Method and apparatus for video filtering

ABSTRACT

Aspects of the disclosure provide methods and apparatuses for video encoding/decoding. In some examples, an apparatus for video decoding includes processing circuitry. The processing circuitry reconstructs a first sample in a video carried in a coded video bitstream based on a non linear mapping based filter with a first filter shape configuration. Then, the processing circuitry determines a switch from the first filter shape configuration to a second filter shape configuration, and reconstructs a second sample in the video based on the non linear mapping based filter with the second filter shape configuration.

INCORPORATION BY REFERENCE

This present disclosure claims the benefit of priority to U.S.Provisional Application No. 63/122,780, “IMPROVED FILTER SHAPE FORSAMPLE OFFSET” filed on Dec. 8, 2020. The entire disclosure of the priorapplication is hereby incorporated by reference in its entirety.

TECHNICAL FIELD

The present disclosure describes embodiments generally related to videocoding.

BACKGROUND

The background description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventors, to the extent the work is described in thisbackground section, as well as aspects of the description that may nototherwise qualify as prior art at the time of filing, are neitherexpressly nor impliedly admitted as prior art against the presentdisclosure.

Video coding and decoding can be performed using inter-pictureprediction with motion compensation. Uncompressed digital video caninclude a series of pictures, each picture having a spatial dimensionof, for example, 1920×1080 luminance samples and associated chrominancesamples. The series of pictures can have a fixed or variable picturerate (informally also known as frame rate), of, for example 60 picturesper second or 60 Hz. Uncompressed video has specific bitraterequirements. For example, 1080p60 4:2:0 video at 8 bit per sample(1920×1080 luminance sample resolution at 60 Hz frame rate) requiresclose to 1.5 Gbit/s bandwidth. An hour of such video requires more than600 GBytes of storage space.

One purpose of video coding and decoding can be the reduction ofredundancy in the input video signal, through compression. Compressioncan help reduce the aforementioned bandwidth and/or storage spacerequirements, in some cases by two orders of magnitude or more. Bothlossless compression and lossy compression, as well as a combinationthereof can be employed. Lossless compression refers to techniques wherean exact copy of the original signal can be reconstructed from thecompressed original signal. When using lossy compression, thereconstructed signal may not be identical to the original signal, butthe distortion between original and reconstructed signals is smallenough to make the reconstructed signal useful for the intendedapplication. In the case of video, lossy compression is widely employed.The amount of distortion tolerated depends on the application; forexample, users of certain consumer streaming applications may toleratehigher distortion than users of television distribution applications.The compression ratio achievable can reflect that: higherallowable/tolerable distortion can yield higher compression ratios.

A video encoder and decoder can utilize techniques from several broadcategories, including, for example, motion compensation, transform,quantization, and entropy coding.

Video codec technologies can include techniques known as intra coding.In intra coding, sample values are represented without reference tosamples or other data from previously reconstructed reference pictures.In some video codecs, the picture is spatially subdivided into blocks ofsamples. When all blocks of samples are coded in intra mode, thatpicture can be an intra picture. Intra pictures and their derivationssuch as independent decoder refresh pictures, can be used to reset thedecoder state and can, therefore, be used as the first picture in acoded video bitstream and a video session, or as a still image. Thesamples of an intra block can be exposed to a transform, and thetransform coefficients can be quantized before entropy coding. Intraprediction can be a technique that minimizes sample values in thepre-transform domain. In some cases, the smaller the DC value after atransform is, and the smaller the AC coefficients are, the fewer thebits that are required at a given quantization step size to representthe block after entropy coding.

Traditional intra coding such as known from, for example MPEG-2generation coding technologies, does not use intra prediction. However,some newer video compression technologies include techniques thatattempt, from, for example, surrounding sample data and/or metadataobtained during the encoding/decoding of spatially neighboring, andpreceding in decoding order, blocks of data. Such techniques arehenceforth called “intra prediction” techniques. Note that in at leastsome cases, intra prediction is using reference data only from thecurrent picture under reconstruction and not from reference pictures.

There can be many different forms of intra prediction. When more thanone of such techniques can be used in a given video coding technology,the technique in use can be coded in an intra prediction mode. Incertain cases, modes can have submodes and/or parameters, and those canbe coded individually or included in the mode codeword. Which codewordto use for a given mode/submode/parameter combination can have an impactin the coding efficiency gain through intra prediction, and so can theentropy coding technology used to translate the codewords into abitstream.

A certain mode of intra prediction was introduced with H.264, refined inH.265, and further refined in newer coding technologies such as jointexploration model (JEM), versatile video coding (VVC), and benchmark set(BMS). A predictor block can be formed using neighboring sample valuesbelonging to already available samples. Sample values of neighboringsamples are copied into the predictor block according to a direction. Areference to the direction in use can be coded in the bitstream or mayitself be predicted.

Referring to FIG. 1A, depicted in the lower right is a subset of ninepredictor directions known from H.265's 33 possible predictor directions(corresponding to the 33 angular modes of the 35 intra modes). The pointwhere the arrows converge (101) represents the sample being predicted.The arrows represent the direction from which the sample is beingpredicted. For example, arrow (102) indicates that sample (101) ispredicted from a sample or samples to the upper right, at a 45 degreeangle from the horizontal. Similarly, arrow (103) indicates that sample(101) is predicted from a sample or samples to the lower left of sample(101), in a 22.5 degree angle from the horizontal.

Still referring to FIG. 1A, on the top left there is depicted a squareblock (104) of 4×4 samples (indicated by a dashed, boldface line). Thesquare block (104) includes 16 samples, each labelled with an “S”, itsposition in the Y dimension (e.g., row index) and its position in the Xdimension (e.g., column index). For example, sample S21 is the secondsample in the Y dimension (from the top) and the first (from the left)sample in the X dimension. Similarly, sample S44 is the fourth sample inblock (104) in both the Y and X dimensions. As the block is 4×4 samplesin size, S44 is at the bottom right. Further shown are reference samplesthat follow a similar numbering scheme. A reference sample is labelledwith an R, its Y position (e.g., row index) and X position (columnindex) relative to block (104). In both H.264 and H.265, predictionsamples neighbor the block under reconstruction; therefore no negativevalues need to be used.

Intra picture prediction can work by copying reference sample valuesfrom the neighboring samples as appropriated by the signaled predictiondirection. For example, assume the coded video bitstream includessignaling that, for this block, indicates a prediction directionconsistent with arrow (102)—that is, samples are predicted from aprediction sample or samples to the upper right, at a 45 degree anglefrom the horizontal. In that case, samples S41, S32, S23, and S14 arepredicted from the same reference sample R05. Sample S44 is thenpredicted from reference sample R08.

In certain cases, the values of multiple reference samples may becombined, for example through interpolation, in order to calculate areference sample; especially when the directions are not evenlydivisible by 45 degrees.

The number of possible directions has increased as video codingtechnology has developed. In H.264 (year 2003), nine different directioncould be represented. That increased to 33 in H.265 (year 2013), andJEM/VVC/BMS, at the time of disclosure, can support up to 65 directions.Experiments have been conducted to identify the most likely directions,and certain techniques in the entropy coding are used to represent thoselikely directions in a small number of bits, accepting a certain penaltyfor less likely directions. Further, the directions themselves cansometimes be predicted from neighboring directions used in neighboring,already decoded, blocks.

FIG. 1B shows a schematic (180) that depicts 65 intra predictiondirections according to JEM to illustrate the increasing number ofprediction directions over time.

The mapping of intra prediction directions bits in the coded videobitstream that represent the direction can be different from videocoding technology to video coding technology; and can range, forexample, from simple direct mappings of prediction direction to intraprediction mode, to codewords, to complex adaptive schemes involvingmost probable modes, and similar techniques. In all cases, however,there can be certain directions that are statistically less likely tooccur in video content than certain other directions. As the goal ofvideo compression is the reduction of redundancy, those less likelydirections will, in a well working video coding technology, berepresented by a larger number of bits than more likely directions.

Motion compensation can be a lossy compression technique and can relateto techniques where a block of sample data from a previouslyreconstructed picture or part thereof (reference picture), after beingspatially shifted in a direction indicated by a motion vector (MVhenceforth), is used for the prediction of a newly reconstructed pictureor picture part. In some cases, the reference picture can be the same asthe picture currently under reconstruction. MVs can have two dimensionsX and Y, or three dimensions, the third being an indication of thereference picture in use (the latter, indirectly, can be a timedimension).

In some video compression techniques, an MV applicable to a certain areaof sample data can be predicted from other MVs, for example from thoserelated to another area of sample data spatially adjacent to the areaunder reconstruction, and preceding that MV in decoding order. Doing socan substantially reduce the amount of data required for coding the MV,thereby removing redundancy and increasing compression. MV predictioncan work effectively, for example, because when coding an input videosignal derived from a camera (known as natural video) there is astatistical likelihood that areas larger than the area to which a singleMV is applicable move in a similar direction and, therefore, can in somecases be predicted using a similar motion vector derived from MVs ofneighboring area. That results in the MV found for a given area to besimilar or the same as the MV predicted from the surrounding MVs, andthat in turn can be represented, after entropy coding, in a smallernumber of bits than what would be used if coding the MV directly. Insome cases, MV prediction can be an example of lossless compression of asignal (namely: the MVs) derived from the original signal (namely: thesample stream). In other cases, MV prediction itself can be lossy, forexample because of rounding errors when calculating a predictor fromseveral surrounding MVs.

Various MV prediction mechanisms are described in H.265/HEVC (ITU-T Rec.H.265, “High Efficiency Video Coding”, December 2016). Out of the manyMV prediction mechanisms that H.265 offers, described here is atechnique henceforth referred to as “spatial merge”.

Referring to FIG. 2 , a current block (201) comprises samples that havebeen found by the encoder during the motion search process to bepredictable from a previous block of the same size that has beenspatially shifted. Instead of coding that MV directly, the MV can bederived from metadata associated with one or more reference pictures,for example from the most recent (in decoding order) reference picture,using the MV associated with either one of five surrounding samples,denoted A0, A1, and B0, B1, B2 (202 through 206, respectively). InH.265, the MV prediction can use predictors from the same referencepicture that the neighboring block is using.

SUMMARY

Aspects of the disclosure provide methods and apparatuses for videoencoding/decoding. In some examples, an apparatus for video decodingincludes processing circuitry. The processing circuitry reconstructs afirst sample in a video carried in a coded video bitstream based on anon linear mapping based filter with a first filter shape configuration.Then, the processing circuitry determines a switch from the first filtershape configuration to a second filter shape configuration, andreconstructs a second sample in the video based on the non linearmapping based filter with the second filter shape configuration.

In an embodiment, the non linear mapping based filter is across-component sample offset (CCSO) filter. In another embodiment, thenon linear mapping based filter is a local sample offset (LSO) filter.

According to an aspect of the disclosure, the first filter shapeconfiguration differs from the second filter shape configuration by atleast one of a geometry shape of filter tap locations, and a distancefrom the filter tap locations to a center of the filter tap locations.

In some examples, the first filter shape configuration and the secondfilter shape configuration respectively have at least one of a crossgeometry shape of filter tap locations and a rectangular geometry shapeof filter tap locations.

In an example, the first filter shape configuration and the secondfilter shape configuration have a same geometry shape and differ by adistance from filter tap locations to a center of the filter taplocations.

In some examples, the processing circuitry decodes an index from thecoded video bitstream that carries the video. The index is indicative ofthe second filter shape configuration. Then, the processing circuitrydetermines the switch from the first filter shape configuration to thesecond filter shape configuration based on the index. In an example, theprocessing circuitry determines the switch from the first filter shapeconfiguration to the second filter shape configuration at a picturelevel. The first sample is in a first picture of the video, and thesecond sample is in a second picture of the video.

In another example, the processing circuitry determines the switch fromthe first filter shape configuration to the second filter shapeconfiguration at a block level. The first sample is in a first block ina picture of the video, the second sample can be in a second block inthe picture of the video.

In some examples, the processing circuitry decodes the index from asyntax signaling of at least one of a block level, a video parameter set(VPS), a sequence parameter set (SPS), a picture parameter set (PPS), anadaptation parameter set (APS), a slice header, a tile header and aframe header.

In some examples, to reconstruct the first sample in the video based onthe non linear mapping based filter with the first filter shapeconfiguration, the processing circuitry can perform a pre-processingoperation on samples at filter tap locations corresponding to the firstfilter shape configuration to generate pre-processed samples, anddetermine an offset to apply on the first sample based on thepre-processed samples. In an example, the processing circuitrycalculates an average sample value at two or more filter tap locationsas a pre-processed sample. In another example, the processing circuitryapplies a filter on a sample at a filter tap location to generate afiltered sample as a pre-processed sample.

Aspects of the disclosure also provide a non-transitorycomputer-readable medium storing instructions which when executed by acomputer for video decoding cause the computer to perform any of themethods for video decoding.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features, the nature, and various advantages of the disclosedsubject matter will be more apparent from the following detaileddescription and the accompanying drawings in which:

FIG. 1A is a schematic illustration of an exemplary subset of intraprediction modes.

FIG. 1B is an illustration of exemplary intra prediction directions.

FIG. 2 is a schematic illustration of a current block and itssurrounding spatial merge candidates in one example.

FIG. 3 is a schematic illustration of a simplified block diagram of acommunication system (300) in accordance with an embodiment.

FIG. 4 is a schematic illustration of a simplified block diagram of acommunication system (400) in accordance with an embodiment.

FIG. 5 is a schematic illustration of a simplified block diagram of adecoder in accordance with an embodiment.

FIG. 6 is a schematic illustration of a simplified block diagram of anencoder in accordance with an embodiment.

FIG. 7 shows a block diagram of an encoder in accordance with anotherembodiment.

FIG. 8 shows a block diagram of a decoder in accordance with anotherembodiment.

FIG. 9 shows examples of filter shapes according to embodiments of thedisclosure.

FIGS. 10A-10D show examples of subsampled positions used for calculatinggradients according to embodiments of the disclosure.

FIGS. 11A-11B show examples of a virtual boundary filtering processaccording to embodiments of the disclosure.

FIGS. 12A-12F show examples of symmetric padding operations at virtualboundaries according to embodiments of the disclosure.

FIG. 13 shows a partition example of a picture according to someembodiments of the disclosure.

FIG. 14 shows a quadtree split pattern for a picture in some examples.

FIG. 15 shows cross-component filters according to an embodiment of thedisclosure.

FIG. 16 shows an example of a filter shape according to an embodiment ofthe disclosure.

FIG. 17 shows a syntax example for cross component filter according tosome embodiments of the disclosure.

FIGS. 18A-18B show exemplary locations of chroma samples relative toluma samples according to embodiments of the disclosure.

FIG. 19 shows an example of direction search according to an embodimentof the disclosure.

FIG. 20 shows an example illustrating subspace projection in someexamples.

FIG. 21 shows a table of a plurality of sample adaptive offset (SAO)types according to an embodiment of the disclosure.

FIG. 22 shows examples of patterns for pixel classification in edgeoffset in some examples.

FIG. 23 shows a table for pixel classification rule for edge offset insome examples.

FIG. 24 shows an example of syntaxes that may be signaled.

FIG. 25 shows an example of a filter support area according to someembodiments of the disclosure.

FIG. 26 shows an example of another filter support area according tosome embodiments of the disclosure.

FIGS. 27A-27C show a table having 81 combinations according to anembodiment of the disclosure.

FIG. 28 shows an example of a filter shape configuration according to anembodiment of the disclosure.

FIG. 29 shows another example of a filter shape configuration accordingto an embodiment of the disclosure.

FIG. 30 shows another example of a filter shape configuration accordingto an embodiment of the disclosure.

FIG. 31 shows another example of a filter shape configuration accordingto an embodiment of the disclosure.

FIG. 32 shows an example of three candidate filter shape configurationsthat have a cross geometry shape.

FIG. 33 shows an example of two candidate filter shape configurationsthat have a cross geometry shape.

FIG. 34 shows an example of two candidate filter shape configurationsthat have a rectangular geometry shape.

FIG. 35 shows an example (3500) of four candidate filter shapeconfigurations that have a mixture of cross geometry shape andrectangular geometry shape.

FIG. 36 shows an example of pre-processing according to an embodiment ofthe disclosure.

FIG. 37 shows another example of pre-processing according to anembodiment of the disclosure.

FIG. 38 shows a flow chart outlining a process according to anembodiment of the disclosure.

FIG. 39 is a schematic illustration of a computer system in accordancewith an embodiment.

DETAILED DESCRIPTION OF EMBODIMENTS

FIG. 3 illustrates a simplified block diagram of a communication system(300) according to an embodiment of the present disclosure. Thecommunication system (300) includes a plurality of terminal devices thatcan communicate with each other, via, for example, a network (350). Forexample, the communication system (300) includes a first pair ofterminal devices (310) and (320) interconnected via the network (350).In the FIG. 3 example, the first pair of terminal devices (310) and(320) performs unidirectional transmission of data. For example, theterminal device (310) may code video data (e.g., a stream of videopictures that are captured by the terminal device (310)) fortransmission to the other terminal device (320) via the network (350).The encoded video data can be transmitted in the form of one or morecoded video bitstreams. The terminal device (320) may receive the codedvideo data from the network (350), decode the coded video data torecover the video pictures and display video pictures according to therecovered video data. Unidirectional data transmission may be common inmedia serving applications and the like.

In another example, the communication system (300) includes a secondpair of terminal devices (330) and (340) that performs bidirectionaltransmission of coded video data that may occur, for example, duringvideoconferencing. For bidirectional transmission of data, in anexample, each terminal device of the terminal devices (330) and (340)may code video data (e.g., a stream of video pictures that are capturedby the terminal device) for transmission to the other terminal device ofthe terminal devices (330) and (340) via the network (350). Eachterminal device of the terminal devices (330) and (340) also may receivethe coded video data transmitted by the other terminal device of theterminal devices (330) and (340), and may decode the coded video data torecover the video pictures and may display video pictures at anaccessible display device according to the recovered video data.

In the FIG. 3 example, the terminal devices (310), (320), (330) and(340) may be illustrated as servers, personal computers and smart phonesbut the principles of the present disclosure may be not so limited.Embodiments of the present disclosure find application with laptopcomputers, tablet computers, media players and/or dedicated videoconferencing equipment. The network (350) represents any number ofnetworks that convey coded video data among the terminal devices (310),(320), (330) and (340), including for example wireline (wired) and/orwireless communication networks. The communication network (350) mayexchange data in circuit-switched and/or packet-switched channels.Representative networks include telecommunications networks, local areanetworks, wide area networks and/or the Internet. For the purposes ofthe present discussion, the architecture and topology of the network(350) may be immaterial to the operation of the present disclosureunless explained herein below.

FIG. 4 illustrates, as an example for an application for the disclosedsubject matter, the placement of a video encoder and a video decoder ina streaming environment. The disclosed subject matter can be equallyapplicable to other video enabled applications, including, for example,video conferencing, digital TV, storing of compressed video on digitalmedia including CD, DVD, memory stick and the like, and so on.

A streaming system may include a capture subsystem (413), that caninclude a video source (401), for example a digital camera, creating forexample a stream of video pictures (402) that are uncompressed. In anexample, the stream of video pictures (402) includes samples that aretaken by the digital camera. The stream of video pictures (402),depicted as a bold line to emphasize a high data volume when compared toencoded video data (404) (or coded video bitstreams), can be processedby an electronic device (420) that includes a video encoder (403)coupled to the video source (401). The video encoder (403) can includehardware, software, or a combination thereof to enable or implementaspects of the disclosed subject matter as described in more detailbelow. The encoded video data (404) (or encoded video bitstream (404)),depicted as a thin line to emphasize the lower data volume when comparedto the stream of video pictures (402), can be stored on a streamingserver (405) for future use. One or more streaming client subsystems,such as client subsystems (406) and (408) in FIG. 4 can access thestreaming server (405) to retrieve copies (407) and (409) of the encodedvideo data (404). A client subsystem (406) can include a video decoder(410), for example, in an electronic device (430). The video decoder(410) decodes the incoming copy (407) of the encoded video data andcreates an outgoing stream of video pictures (411) that can be renderedon a display (412) (e.g., display screen) or other rendering device (notdepicted). In some streaming systems, the encoded video data (404),(407), and (409) (e.g., video bitstreams) can be encoded according tocertain video coding/compression standards. Examples of those standardsinclude ITU-T Recommendation H.265. In an example, a video codingstandard under development is informally known as Versatile Video Coding(VVC). The disclosed subject matter may be used in the context of VVC.

It is noted that the electronic devices (420) and (430) can includeother components (not shown). For example, the electronic device (420)can include a video decoder (not shown) and the electronic device (430)can include a video encoder (not shown) as well.

FIG. 5 shows a block diagram of a video decoder (510) according to anembodiment of the present disclosure. The video decoder (510) can beincluded in an electronic device (530). The electronic device (530) caninclude a receiver (531) (e.g., receiving circuitry). The video decoder(510) can be used in the place of the video decoder (410) in the FIG. 4example.

The receiver (531) may receive one or more coded video sequences to bedecoded by the video decoder (510); in the same or another embodiment,one coded video sequence at a time, where the decoding of each codedvideo sequence is independent from other coded video sequences. Thecoded video sequence may be received from a channel (501), which may bea hardware/software link to a storage device which stores the encodedvideo data. The receiver (531) may receive the encoded video data withother data, for example, coded audio data and/or ancillary data streams,that may be forwarded to their respective using entities (not depicted).The receiver (531) may separate the coded video sequence from the otherdata. To combat network jitter, a buffer memory (515) may be coupled inbetween the receiver (531) and an entropy decoder/parser (520) (“parser(520)” henceforth). In certain applications, the buffer memory (515) ispart of the video decoder (510). In others, it can be outside of thevideo decoder (510) (not depicted). In still others, there can be abuffer memory (not depicted) outside of the video decoder (510), forexample to combat network jitter, and in addition another buffer memory(515) inside the video decoder (510), for example to handle playouttiming. When the receiver (531) is receiving data from a store/forwarddevice of sufficient bandwidth and controllability, or from anisosynchronous network, the buffer memory (515) may not be needed, orcan be small. For use on best effort packet networks such as theInternet, the buffer memory (515) may be required, can be comparativelylarge and can be advantageously of adaptive size, and may at leastpartially be implemented in an operating system or similar elements (notdepicted) outside of the video decoder (510).

The video decoder (510) may include the parser (520) to reconstructsymbols (521) from the coded video sequence. Categories of those symbolsinclude information used to manage operation of the video decoder (510),and potentially information to control a rendering device such as arender device (512) (e.g., a display screen) that is not an integralpart of the electronic device (530) but can be coupled to the electronicdevice (530), as was shown in FIG. 5 . The control information for therendering device(s) may be in the form of Supplemental EnhancementInformation (SEI messages) or Video Usability Information (VUI)parameter set fragments (not depicted). The parser (520) mayparse/entropy-decode the coded video sequence that is received. Thecoding of the coded video sequence can be in accordance with a videocoding technology or standard, and can follow various principles,including variable length coding, Huffman coding, arithmetic coding withor without context sensitivity, and so forth. The parser (520) mayextract from the coded video sequence, a set of subgroup parameters forat least one of the subgroups of pixels in the video decoder, based uponat least one parameter corresponding to the group. Subgroups can includeGroups of Pictures (GOPs), pictures, tiles, slices, macroblocks, CodingUnits (CUs), blocks, Transform Units (TUs), Prediction Units (PUs) andso forth. The parser (520) may also extract from the coded videosequence information such as transform coefficients, quantizer parametervalues, motion vectors, and so forth.

The parser (520) may perform an entropy decoding/parsing operation onthe video sequence received from the buffer memory (515), so as tocreate symbols (521).

Reconstruction of the symbols (521) can involve multiple different unitsdepending on the type of the coded video picture or parts thereof (suchas: inter and intra picture, inter and intra block), and other factors.Which units are involved, and how, can be controlled by the subgroupcontrol information that was parsed from the coded video sequence by theparser (520). The flow of such subgroup control information between theparser (520) and the multiple units below is not depicted for clarity.

Beyond the functional blocks already mentioned, the video decoder (510)can be conceptually subdivided into a number of functional units asdescribed below. In a practical implementation operating undercommercial constraints, many of these units interact closely with eachother and can, at least partly, be integrated into each other. However,for the purpose of describing the disclosed subject matter, theconceptual subdivision into the functional units below is appropriate.

A first unit is the scaler/inverse transform unit (551). Thescaler/inverse transform unit (551) receives a quantized transformcoefficient as well as control information, including which transform touse, block size, quantization factor, quantization scaling matrices,etc. as symbol(s) (521) from the parser (520). The scaler/inversetransform unit (551) can output blocks comprising sample values, thatcan be input into aggregator (555).

In some cases, the output samples of the scaler/inverse transform (551)can pertain to an intra coded block; that is: a block that is not usingpredictive information from previously reconstructed pictures, but canuse predictive information from previously reconstructed parts of thecurrent picture. Such predictive information can be provided by an intrapicture prediction unit (552). In some cases, the intra pictureprediction unit (552) generates a block of the same size and shape ofthe block under reconstruction, using surrounding already reconstructedinformation fetched from the current picture buffer (558). The currentpicture buffer (558) buffers, for example, partly reconstructed currentpicture and/or fully reconstructed current picture. The aggregator(555), in some cases, adds, on a per sample basis, the predictioninformation the intra prediction unit (552) has generated to the outputsample information as provided by the scaler/inverse transform unit(551).

In other cases, the output samples of the scaler/inverse transform unit(551) can pertain to an inter coded, and potentially motion compensatedblock. In such a case, a motion compensation prediction unit (553) canaccess reference picture memory (557) to fetch samples used forprediction. After motion compensating the fetched samples in accordancewith the symbols (521) pertaining to the block, these samples can beadded by the aggregator (555) to the output of the scaler/inversetransform unit (551) (in this case called the residual samples orresidual signal) so as to generate output sample information. Theaddresses within the reference picture memory (557) from where themotion compensation prediction unit (553) fetches prediction samples canbe controlled by motion vectors, available to the motion compensationprediction unit (553) in the form of symbols (521) that can have, forexample X, Y, and reference picture components. Motion compensation alsocan include interpolation of sample values as fetched from the referencepicture memory (557) when sub-sample exact motion vectors are in use,motion vector prediction mechanisms, and so forth.

The output samples of the aggregator (555) can be subject to variousloop filtering techniques in the loop filter unit (556). Videocompression technologies can include in-loop filter technologies thatare controlled by parameters included in the coded video sequence (alsoreferred to as coded video bitstream) and made available to the loopfilter unit (556) as symbols (521) from the parser (520), but can alsobe responsive to meta-information obtained during the decoding ofprevious (in decoding order) parts of the coded picture or coded videosequence, as well as responsive to previously reconstructed andloop-filtered sample values.

The output of the loop filter unit (556) can be a sample stream that canbe output to the render device (512) as well as stored in the referencepicture memory (557) for use in future inter-picture prediction.

Certain coded pictures, once fully reconstructed, can be used asreference pictures for future prediction. For example, once a codedpicture corresponding to a current picture is fully reconstructed andthe coded picture has been identified as a reference picture (by, forexample, the parser (520)), the current picture buffer (558) can becomea part of the reference picture memory (557), and a fresh currentpicture buffer can be reallocated before commencing the reconstructionof the following coded picture.

The video decoder (510) may perform decoding operations according to apredetermined video compression technology in a standard, such as ITU-TRec. H.265. The coded video sequence may conform to a syntax specifiedby the video compression technology or standard being used, in the sensethat the coded video sequence adheres to both the syntax of the videocompression technology or standard and the profiles as documented in thevideo compression technology or standard. Specifically, a profile canselect certain tools as the only tools available for use under thatprofile from all the tools available in the video compression technologyor standard. Also necessary for compliance can be that the complexity ofthe coded video sequence is within bounds as defined by the level of thevideo compression technology or standard. In some cases, levels restrictthe maximum picture size, maximum frame rate, maximum reconstructionsample rate (measured in, for example megasamples per second), maximumreference picture size, and so on. Limits set by levels can, in somecases, be further restricted through Hypothetical Reference Decoder(HRD) specifications and metadata for HRD buffer management signaled inthe coded video sequence.

In an embodiment, the receiver (531) may receive additional (redundant)data with the encoded video. The additional data may be included as partof the coded video sequence(s). The additional data may be used by thevideo decoder (510) to properly decode the data and/or to moreaccurately reconstruct the original video data. Additional data can bein the form of, for example, temporal, spatial, or signal noise ratio(SNR) enhancement layers, redundant slices, redundant pictures, forwarderror correction codes, and so on.

FIG. 6 shows a block diagram of a video encoder (603) according to anembodiment of the present disclosure. The video encoder (603) isincluded in an electronic device (620). The electronic device (620)includes a transmitter (640) (e.g., transmitting circuitry). The videoencoder (603) can be used in the place of the video encoder (403) in theFIG. 4 example.

The video encoder (603) may receive video samples from a video source(601) (that is not part of the electronic device (620) in the FIG. 6example) that may capture video image(s) to be coded by the videoencoder (603). In another example, the video source (601) is a part ofthe electronic device (620).

The video source (601) may provide the source video sequence to be codedby the video encoder (603) in the form of a digital video sample streamthat can be of any suitable bit depth (for example: 8 bit, 10 bit, 12bit, . . . ), any color space (for example, BT.601 Y CrCB, RGB, . . . ),and any suitable sampling structure (for example Y CrCb 4:2:0, Y CrCb4:4:4). In a media serving system, the video source (601) may be astorage device storing previously prepared video. In a videoconferencingsystem, the video source (601) may be a camera that captures local imageinformation as a video sequence. Video data may be provided as aplurality of individual pictures that impart motion when viewed insequence. The pictures themselves may be organized as a spatial array ofpixels, wherein each pixel can comprise one or more samples depending onthe sampling structure, color space, etc. in use. A person skilled inthe art can readily understand the relationship between pixels andsamples. The description below focuses on samples.

According to an embodiment, the video encoder (603) may code andcompress the pictures of the source video sequence into a coded videosequence (643) in real time or under any other time constraints asrequired by the application. Enforcing appropriate coding speed is onefunction of a controller (650). In some embodiments, the controller(650) controls other functional units as described below and isfunctionally coupled to the other functional units. The coupling is notdepicted for clarity. Parameters set by the controller (650) can includerate control related parameters (picture skip, quantizer, lambda valueof rate-distortion optimization techniques, . . . ), picture size, groupof pictures (GOP) layout, maximum motion vector search range, and soforth. The controller (650) can be configured to have other suitablefunctions that pertain to the video encoder (603) optimized for acertain system design.

In some embodiments, the video encoder (603) is configured to operate ina coding loop. As an oversimplified description, in an example, thecoding loop can include a source coder (630) (e.g., responsible forcreating symbols, such as a symbol stream, based on an input picture tobe coded, and a reference picture(s)), and a (local) decoder (633)embedded in the video encoder (603). The decoder (633) reconstructs thesymbols to create the sample data in a similar manner as a (remote)decoder also would create (as any compression between symbols and codedvideo bitstream is lossless in the video compression technologiesconsidered in the disclosed subject matter). The reconstructed samplestream (sample data) is input to the reference picture memory (634). Asthe decoding of a symbol stream leads to bit-exact results independentof decoder location (local or remote), the content in the referencepicture memory (634) is also bit exact between the local encoder andremote encoder. In other words, the prediction part of an encoder “sees”as reference picture samples exactly the same sample values as a decoderwould “see” when using prediction during decoding. This fundamentalprinciple of reference picture synchronicity (and resulting drift, ifsynchronicity cannot be maintained, for example because of channelerrors) is used in some related arts as well.

The operation of the “local” decoder (633) can be the same as of a“remote” decoder, such as the video decoder (510), which has alreadybeen described in detail above in conjunction with FIG. 5 . Brieflyreferring also to FIG. 5 , however, as symbols are available andencoding/decoding of symbols to a coded video sequence by an entropycoder (645) and the parser (520) can be lossless, the entropy decodingparts of the video decoder (510), including the buffer memory (515), andparser (520) may not be fully implemented in the local decoder (633).

An observation that can be made at this point is that any decodertechnology except the parsing/entropy decoding that is present in adecoder also necessarily needs to be present, in substantially identicalfunctional form, in a corresponding encoder. For this reason, thedisclosed subject matter focuses on decoder operation. The descriptionof encoder technologies can be abbreviated as they are the inverse ofthe comprehensively described decoder technologies. Only in certainareas a more detail description is required and provided below.

During operation, in some examples, the source coder (630) may performmotion compensated predictive coding, which codes an input picturepredictively with reference to one or more previously coded picture fromthe video sequence that were designated as “reference pictures.” In thismanner, the coding engine (632) codes differences between pixel blocksof an input picture and pixel blocks of reference picture(s) that may beselected as prediction reference(s) to the input picture.

The local video decoder (633) may decode coded video data of picturesthat may be designated as reference pictures, based on symbols createdby the source coder (630). Operations of the coding engine (632) mayadvantageously be lossy processes. When the coded video data may bedecoded at a video decoder (not shown in FIG. 6 ), the reconstructedvideo sequence typically may be a replica of the source video sequencewith some errors. The local video decoder (633) replicates decodingprocesses that may be performed by the video decoder on referencepictures and may cause reconstructed reference pictures to be stored inthe reference picture cache (634). In this manner, the video encoder(603) may store copies of reconstructed reference pictures locally thathave common content as the reconstructed reference pictures that will beobtained by a far-end video decoder (absent transmission errors).

The predictor (635) may perform prediction searches for the codingengine (632). That is, for a new picture to be coded, the predictor(635) may search the reference picture memory (634) for sample data (ascandidate reference pixel blocks) or certain metadata such as referencepicture motion vectors, block shapes, and so on, that may serve as anappropriate prediction reference for the new pictures. The predictor(635) may operate on a sample block-by-pixel block basis to findappropriate prediction references. In some cases, as determined bysearch results obtained by the predictor (635), an input picture mayhave prediction references drawn from multiple reference pictures storedin the reference picture memory (634).

The controller (650) may manage coding operations of the source coder(630), including, for example, setting of parameters and subgroupparameters used for encoding the video data.

Output of all aforementioned functional units may be subjected toentropy coding in the entropy coder (645). The entropy coder (645)translates the symbols as generated by the various functional units intoa coded video sequence, by lossless compressing the symbols according totechnologies such as Huffman coding, variable length coding, arithmeticcoding, and so forth.

The transmitter (640) may buffer the coded video sequence(s) as createdby the entropy coder (645) to prepare for transmission via acommunication channel (660), which may be a hardware/software link to astorage device which would store the encoded video data. The transmitter(640) may merge coded video data from the video coder (603) with otherdata to be transmitted, for example, coded audio data and/or ancillarydata streams (sources not shown).

The controller (650) may manage operation of the video encoder (603).During coding, the controller (650) may assign to each coded picture acertain coded picture type, which may affect the coding techniques thatmay be applied to the respective picture. For example, pictures oftenmay be assigned as one of the following picture types:

An Intra Picture (I picture) may be one that may be coded and decodedwithout using any other picture in the sequence as a source ofprediction. Some video codecs allow for different types of intrapictures, including, for example Independent Decoder Refresh (“IDR”)Pictures. A person skilled in the art is aware of those variants of Ipictures and their respective applications and features.

A predictive picture (P picture) may be one that may be coded anddecoded using intra prediction or inter prediction using at most onemotion vector and reference index to predict the sample values of eachblock.

A bi-directionally predictive picture (B Picture) may be one that may becoded and decoded using intra prediction or inter prediction using atmost two motion vectors and reference indices to predict the samplevalues of each block. Similarly, multiple-predictive pictures can usemore than two reference pictures and associated metadata for thereconstruction of a single block.

Source pictures commonly may be subdivided spatially into a plurality ofsample blocks (for example, blocks of 4×4, 8×8, 4×8, or 16×16 sampleseach) and coded on a block-by-block basis. Blocks may be codedpredictively with reference to other (already coded) blocks asdetermined by the coding assignment applied to the blocks' respectivepictures. For example, blocks of I pictures may be codednon-predictively or they may be coded predictively with reference toalready coded blocks of the same picture (spatial prediction or intraprediction). Pixel blocks of P pictures may be coded predictively, viaspatial prediction or via temporal prediction with reference to onepreviously coded reference picture. Blocks of B pictures may be codedpredictively, via spatial prediction or via temporal prediction withreference to one or two previously coded reference pictures.

The video encoder (603) may perform coding operations according to apredetermined video coding technology or standard, such as ITU-T Rec.H.265. In its operation, the video encoder (603) may perform variouscompression operations, including predictive coding operations thatexploit temporal and spatial redundancies in the input video sequence.The coded video data, therefore, may conform to a syntax specified bythe video coding technology or standard being used.

In an embodiment, the transmitter (640) may transmit additional datawith the encoded video. The source coder (630) may include such data aspart of the coded video sequence. Additional data may comprisetemporal/spatial/SNR enhancement layers, other forms of redundant datasuch as redundant pictures and slices, SEI messages, VUI parameter setfragments, and so on.

A video may be captured as a plurality of source pictures (videopictures) in a temporal sequence. Intra-picture prediction (oftenabbreviated to intra prediction) makes use of spatial correlation in agiven picture, and inter-picture prediction makes uses of the (temporalor other) correlation between the pictures. In an example, a specificpicture under encoding/decoding, which is referred to as a currentpicture, is partitioned into blocks. When a block in the current pictureis similar to a reference block in a previously coded and still bufferedreference picture in the video, the block in the current picture can becoded by a vector that is referred to as a motion vector. The motionvector points to the reference block in the reference picture, and canhave a third dimension identifying the reference picture, in casemultiple reference pictures are in use.

In some embodiments, a bi-prediction technique can be used in theinter-picture prediction. According to the bi-prediction technique, tworeference pictures, such as a first reference picture and a secondreference picture that are both prior in decoding order to the currentpicture in the video (but may be in the past and future, respectively,in display order) are used. A block in the current picture can be codedby a first motion vector that points to a first reference block in thefirst reference picture, and a second motion vector that points to asecond reference block in the second reference picture. The block can bepredicted by a combination of the first reference block and the secondreference block.

Further, a merge mode technique can be used in the inter-pictureprediction to improve coding efficiency.

According to some embodiments of the disclosure, predictions, such asinter-picture predictions and intra-picture predictions are performed inthe unit of blocks. For example, according to the HEVC standard, apicture in a sequence of video pictures is partitioned into coding treeunits (CTU) for compression, the CTUs in a picture have the same size,such as 64×64 pixels, 32×32 pixels, or 16×16 pixels. In general, a CTUincludes three coding tree blocks (CTBs), which are one luma CTB and twochroma CTBs. Each CTU can be recursively quadtree split into one ormultiple coding units (CUs). For example, a CTU of 64×64 pixels can besplit into one CU of 64×64 pixels, or 4 CUs of 32×32 pixels, or 16 CUsof 16×16 pixels. In an example, each CU is analyzed to determine aprediction type for the CU, such as an inter prediction type or an intraprediction type. The CU is split into one or more prediction units (PUs)depending on the temporal and/or spatial predictability. Generally, eachPU includes a luma prediction block (PB), and two chroma PBs. In anembodiment, a prediction operation in coding (encoding/decoding) isperformed in the unit of a prediction block. Using a luma predictionblock as an example of a prediction block, the prediction block includesa matrix of values (e.g., luma values) for pixels, such as 8×8 pixels,16×16 pixels, 8×16 pixels, 16×8 pixels, and the like.

FIG. 7 shows a diagram of a video encoder (703) according to anotherembodiment of the disclosure. The video encoder (703) is configured toreceive a processing block (e.g., a prediction block) of sample valueswithin a current video picture in a sequence of video pictures, andencode the processing block into a coded picture that is part of a codedvideo sequence. In an example, the video encoder (703) is used in theplace of the video encoder (403) in the FIG. 4 example.

In an HEVC example, the video encoder (703) receives a matrix of samplevalues for a processing block, such as a prediction block of 8×8samples, and the like. The video encoder (703) determines whether theprocessing block is best coded using intra mode, inter mode, orbi-prediction mode using, for example, rate-distortion optimization.When the processing block is to be coded in intra mode, the videoencoder (703) may use an intra prediction technique to encode theprocessing block into the coded picture; and when the processing blockis to be coded in inter mode or bi-prediction mode, the video encoder(703) may use an inter prediction or bi-prediction technique,respectively, to encode the processing block into the coded picture. Incertain video coding technologies, merge mode can be an inter pictureprediction submode where the motion vector is derived from one or moremotion vector predictors without the benefit of a coded motion vectorcomponent outside the predictors. In certain other video codingtechnologies, a motion vector component applicable to the subject blockmay be present. In an example, the video encoder (703) includes othercomponents, such as a mode decision module (not shown) to determine themode of the processing blocks.

In the FIG. 7 example, the video encoder (703) includes the interencoder (730), an intra encoder (722), a residue calculator (723), aswitch (726), a residue encoder (724), a general controller (721), andan entropy encoder (725) coupled together as shown in FIG. 7 .

The inter encoder (730) is configured to receive the samples of thecurrent block (e.g., a processing block), compare the block to one ormore reference blocks in reference pictures (e.g., blocks in previouspictures and later pictures), generate inter prediction information(e.g., description of redundant information according to inter encodingtechnique, motion vectors, merge mode information), and calculate interprediction results (e.g., predicted block) based on the inter predictioninformation using any suitable technique. In some examples, thereference pictures are decoded reference pictures that are decoded basedon the encoded video information.

The intra encoder (722) is configured to receive the samples of thecurrent block (e.g., a processing block), in some cases compare theblock to blocks already coded in the same picture, generate quantizedcoefficients after transform, and in some cases also intra predictioninformation (e.g., an intra prediction direction information accordingto one or more intra encoding techniques). In an example, the intraencoder (722) also calculates intra prediction results (e.g., predictedblock) based on the intra prediction information and reference blocks inthe same picture.

The general controller (721) is configured to determine general controldata and control other components of the video encoder (703) based onthe general control data. In an example, the general controller (721)determines the mode of the block, and provides a control signal to theswitch (726) based on the mode. For example, when the mode is the intramode, the general controller (721) controls the switch (726) to selectthe intra mode result for use by the residue calculator (723), andcontrols the entropy encoder (725) to select the intra predictioninformation and include the intra prediction information in thebitstream; and when the mode is the inter mode, the general controller(721) controls the switch (726) to select the inter prediction resultfor use by the residue calculator (723), and controls the entropyencoder (725) to select the inter prediction information and include theinter prediction information in the bitstream.

The residue calculator (723) is configured to calculate a difference(residue data) between the received block and prediction resultsselected from the intra encoder (722) or the inter encoder (730). Theresidue encoder (724) is configured to operate based on the residue datato encode the residue data to generate the transform coefficients. In anexample, the residue encoder (724) is configured to convert the residuedata from a spatial domain to a frequency domain, and generate thetransform coefficients. The transform coefficients are then subject toquantization processing to obtain quantized transform coefficients. Invarious embodiments, the video encoder (703) also includes a residuedecoder (728). The residue decoder (728) is configured to performinverse-transform, and generate the decoded residue data. The decodedresidue data can be suitably used by the intra encoder (722) and theinter encoder (730). For example, the inter encoder (730) can generatedecoded blocks based on the decoded residue data and inter predictioninformation, and the intra encoder (722) can generate decoded blocksbased on the decoded residue data and the intra prediction information.The decoded blocks are suitably processed to generate decoded picturesand the decoded pictures can be buffered in a memory circuit (not shown)and used as reference pictures in some examples.

The entropy encoder (725) is configured to format the bitstream toinclude the encoded block. The entropy encoder (725) is configured toinclude various information according to a suitable standard, such asthe HEVC standard. In an example, the entropy encoder (725) isconfigured to include the general control data, the selected predictioninformation (e.g., intra prediction information or inter predictioninformation), the residue information, and other suitable information inthe bitstream. Note that, according to the disclosed subject matter,when coding a block in the merge submode of either inter mode orbi-prediction mode, there is no residue information.

FIG. 8 shows a diagram of a video decoder (810) according to anotherembodiment of the disclosure. The video decoder (810) is configured toreceive coded pictures that are part of a coded video sequence, anddecode the coded pictures to generate reconstructed pictures. In anexample, the video decoder (810) is used in the place of the videodecoder (410) in the FIG. 4 example.

In the FIG. 8 example, the video decoder (810) includes an entropydecoder (871), an inter decoder (880), a residue decoder (873), areconstruction module (874), and an intra decoder (872) coupled togetheras shown in FIG. 8 .

The entropy decoder (871) can be configured to reconstruct, from thecoded picture, certain symbols that represent the syntax elements ofwhich the coded picture is made up. Such symbols can include, forexample, the mode in which a block is coded (such as, for example, intramode, inter mode, bi-predicted mode, the latter two in merge submode oranother submode), prediction information (such as, for example, intraprediction information or inter prediction information) that canidentify certain sample or metadata that is used for prediction by theintra decoder (872) or the inter decoder (880), respectively, residualinformation in the form of, for example, quantized transformcoefficients, and the like. In an example, when the prediction mode isinter or bi-predicted mode, the inter prediction information is providedto the inter decoder (880); and when the prediction type is the intraprediction type, the intra prediction information is provided to theintra decoder (872). The residual information can be subject to inversequantization and is provided to the residue decoder (873).

The inter decoder (880) is configured to receive the inter predictioninformation, and generate inter prediction results based on the interprediction information.

The intra decoder (872) is configured to receive the intra predictioninformation, and generate prediction results based on the intraprediction information.

The residue decoder (873) is configured to perform inverse quantizationto extract de-quantized transform coefficients, and process thede-quantized transform coefficients to convert the residual from thefrequency domain to the spatial domain. The residue decoder (873) mayalso require certain control information (to include the QuantizerParameter (QP)), and that information may be provided by the entropydecoder (871) (data path not depicted as this may be low volume controlinformation only).

The reconstruction module (874) is configured to combine, in the spatialdomain, the residual as output by the residue decoder (873) and theprediction results (as output by the inter or intra prediction modulesas the case may be) to form a reconstructed block, that may be part ofthe reconstructed picture, which in turn may be part of thereconstructed video. It is noted that other suitable operations, such asa deblocking operation and the like, can be performed to improve thevisual quality.

It is noted that the video encoders (403), (603), and (703), and thevideo decoders (410), (510), and (810) can be implemented using anysuitable technique. In an embodiment, the video encoders (403), (603),and (703), and the video decoders (410), (510), and (810) can beimplemented using one or more integrated circuits. In anotherembodiment, the video encoders (403), (603), and (603), and the videodecoders (410), (510), and (810) can be implemented using one or moreprocessors that execute software instructions.

Aspects of the disclosure provide filtering techniques for videocoding/decoding.

An adaptive loop filter (ALF) with block-based filter adaption can beapplied by encoders/decoders to reduce artifacts. For a luma component,one of a plurality of filters (e.g., 25 filters) can be selected for a4×4 luma block, for example, based on a direction and activity of localgradients.

An ALF can have any suitable shape and size. Referring to FIG. 9 , ALFs(910)-(911) have a diamond shape, such as a 5×5 diamond-shape for theALF (910) and a 7×7 diamond-shape for the ALF (911). In the ALF (910),elements (920)-(932) form a diamond shape and can be used in thefiltering process. Seven values (e.g., C0-C6) can be used for theelements (920)-(932). In the ALF (911), elements (940)-(964) forms adiamond shape and can be used in the filtering process. Thirteen values(e.g., C0-C12) can be used for the elements (940)-(964).

Referring to FIG. 9 , in some examples, the two ALFs (910)-(911) withthe diamond filter shape are used. The 5×5 diamond-shaped filter (910)can be applied for chroma components (e.g., chroma blocks, chroma CBs),and the 7×7 diamond-shaped filter (911) can be applied for a lumacomponent (e.g., a luma block, a luma CB). Other suitable shape(s) andsize(s) can be used in the ALF. For example, a 9×9 diamond-shaped filtercan be used.

Filter coefficients at locations indicated by the values (e.g., C0-C6 in(910) or C0-C12 in (920)) can be non-zero. Further, when the ALFincludes a clipping function, clipping values at the locations can benon-zero.

For block classification of a luma component, a 4×4 block (or lumablock, luma CB) can be categorized or classified as one of multiple(e.g., 25) classes. A classification index C can be derived based on adirectionality parameter D and a quantized value Â of an activity valueA using Eq. (1).C=5D+Â  Eq. (1)To calculate the directionality parameter D and the quantized value Â,gradients g_(v), g_(h), g_(d1), and g_(d2) of a vertical, a horizontal,and two diagonal directions (e.g., d1 and d2), respectively, can becalculated using 1-D Laplacian as follows.

$\begin{matrix}{{g_{v} = {\sum\limits_{k = {i - 2}}^{i + 3}{\sum\limits_{l = {j - 2}}^{j + 3}V_{k,l}}}},{V_{k,l} = {❘{{2{R( {k,l} )}} - {R( {k,{l - 1}} )} - {R( {k,{l + 1}} )}}❘}}} & {{Eq}.(2)}\end{matrix}$ $\begin{matrix}{{g_{h} = {\sum\limits_{k = {i - 2}}^{i + 3}{\sum\limits_{l = {j - 2}}^{j + 3}H_{k,l}}}},{H_{k,l} = {❘{{2{R( {k,l} )}} - {R( {{k - 1},l} )} - {R( {{k + 1},l} )}}❘}}} & {{Eq}.(3)}\end{matrix}$ $\begin{matrix}{{g_{d1} = {\sum\limits_{k = {i - 2}}^{i + 3}{\sum\limits_{l = {j - 3}}^{j + 3}{D1_{k,l}}}}},{{D1_{k,l}} = {❘{{2{R( {k,l} )}} - {R( {{k - 1},{l - 1}} )} - {R( {{k + 1},{l + 1}} )}}❘}}} & {{Eq}.(4)}\end{matrix}$ $\begin{matrix}{{g_{d2} = {\sum\limits_{k = {i - 2}}^{i + 3}{\sum\limits_{j = {j - 2}}^{j + 3}{D2_{k,l}}}}},{{D2_{k,l}} = {❘{{2{R( {k,l} )}} - {R( {{k - 1},{l + 1}} )} - {R( {{k + 1},{l - 1}} )}}❘}}} & {{Eq}.(5)}\end{matrix}$where indices i and j refer to coordinates of an upper left samplewithin the 4×4 block and R(k,l) indicates a reconstructed sample at acoordinate (k,l). The directions (e.g., d1 and d2) can refer to 2diagonal directions.

To reduce complexity of the block classification described above, asubsampled 1-D Laplacian calculation can be applied. FIGS. 10A-10D showexamples of subsampled positions used for calculating the gradientsg_(v), g_(h), g_(d1), and g_(d2) of the vertical (FIG. 10A), thehorizontal (FIG. 10B), and the two diagonal directions d1 (FIG. 10C) andd2 (FIG. 10D), respectively. The same subsampled positions can be usedfor gradient calculation of the different directions. In FIG. 10A,labels ‘V’ show the subsampled positions to calculate the verticalgradient g_(v). In FIG. 10B, labels ‘H’ show the subsampled positions tocalculate the horizontal gradient g_(h). In FIG. 10C, labels ‘D1’ showthe subsampled positions to calculate the d1 diagonal gradient g_(d1).In FIG. 10D, labels ‘D2’ show the subsampled positions to calculate thed2 diagonal gradient g_(d2).

A maximum value g_(h,v) ^(max) and a minimum value g_(h,v) ^(min) of thegradients of horizontal and vertical directions g_(v) and g_(h) can beset as:g _(h,v) ^(max)=max(g _(h) ,g _(v)), g _(h,v) ^(min)=min(g _(h) ,g_(v))  Eq. (6)A maximum value g_(d1,d2) ^(max) and a minimum value g_(d1,d2) ^(min) ofthe gradients of two diagonal directions g_(d1) and g_(d2) can be setas:g _(d1,d2) ^(max)=max(g _(d1) ,g _(d2)), g _(d1,d2) ^(min)=min(g _(d1),g _(d2))  Eq. (7)The directionality parameter D can be derived based on the above valuesand two thresholds t₁ and t₂ as below.Step 1. If (1) g_(h,v) ^(max)≤t₁·g_(h,v) ^(min) and (2) g_(d1,d2)^(max)≤t₁·g_(d1,d2) ^(min) are true, D is set to 0.Step 2. If g_(h,v) ^(max)/g_(h,v) ^(min)>g_(d1,d2) ^(max)/g_(d1,d2)^(min), continue to Step 3; otherwise continue to Step 4.Step 3. If g_(h,v) ^(max)>t₂·g_(h,v) ^(min), D is set to 2; otherwise Dis set to 1.Step 4. If g_(d1,d2) ^(max)>t₂·g_(d1,d2) ^(min), D is set to 4;otherwise D is set to 3.

The activity value A can be calculated as:

$\begin{matrix}{A = {{\sum\limits_{k = {i - 2}}^{i + 3}{\sum\limits_{l = {j - 2}}^{j + 3}( {V_{k,l} + H_{k,l}} )}} = {g_{v} + g_{h}}}} & {{Eq}.(8)}\end{matrix}$A can be further quantized to a range of 0 to 4, inclusively, and thequantized value is denoted as Â.

For chroma components in a picture, no block classification is applied,and thus a single set of ALF coefficients can be applied for each chromacomponent.

Geometric transformations can be applied to filter coefficients andcorresponding filter clipping values (also referred to as clippingvalues). Before filtering a block (e.g., a 4×4 luma block), geometrictransformations such as rotation or diagonal and vertical flipping canbe applied to the filter coefficients f(k, l) and the correspondingfilter clipping values c(k, l), for example, depending on gradientvalues (e.g., g_(v), g_(h), g_(d1), and/or g_(d2)) calculated for theblock. The geometric transformations applied to the filter coefficientsf(k, l) and the corresponding filter clipping values c(k, l) can beequivalent to applying the geometric transformations to samples in aregion supported by the filter. The geometric transformations can makedifferent blocks to which an ALF is applied more similar by aligning therespective directionality.

Three geometric transformations, including a diagonal flip, a verticalflip, and a rotation can be performed as described by Eqs. (9)-(11),respectively.f _(D)(k,l)=f(l,k),c _(D)(k,l)=c(l,k),  Eq. (9)f _(V)(k,l)=f(k,K−l−1),c _(V)(k,l)=c(k,K−l−1)  Eq. (10)f _(R)(k,l)=f(K−l−1,k),c _(R)(k,l)=c(K−l−1,k)  Eq. (11)where K is a size of the ALF or the filter, and 0≤k,l≤K−1 arecoordinates of coefficients. For example, a location (0,0) is at anupper left corner and a location (K−1,K−1) is at a lower right corner ofthe filter f or a clipping value matrix (or clipping matrix) c. Thetransformations can be applied to the filter coefficients f (k, l) andthe clipping values c(k, l) depending on the gradient values calculatedfor the block. An example of a relationship between the transformationand the four gradients are summarized in Table 1.

TABLE 1 Mapping of the gradient calculated for a block and thetransformation Gradient values Transformation g_(d2) < g_(d1) and g_(h)< g_(v) No transformation g_(d2) < g_(d1) and g_(v) < g_(h) Diagonalflip g_(d1) < g_(d2) and g_(h) < g_(v) Vertical flip g_(d1) < g_(d2) andg_(v) < g_(h) Rotation

In some embodiments, ALF filter parameters are signaled in an AdaptationParameter Set (APS) for a picture. In the APS, one or more sets (e.g.,up to 25 sets) of luma filter coefficients and clipping value indexescan be signaled. In an example, a set of the one or more sets caninclude luma filter coefficients and one or more clipping value indexes.One or more sets (e.g., up to 8 sets) of chroma filter coefficients andclipping value indexes can be signaled. To reduce signaling overhead,filter coefficients of different classifications (e.g., having differentclassification indices) for luma components can be merged. In a sliceheader, indices of the APSs used for a current slice can be signaled.

In an embodiment, a clipping value index (also referred to as clippingindex) can be decoded from the APS. The clipping value index can be usedto determine a corresponding clipping value, for example, based on arelationship between the clipping value index and the correspondingclipping value. The relationship can be pre-defined and stored in adecoder. In an example, the relationship is described by a table, suchas a luma table (e.g., used for a luma CB) of the clipping value indexand the corresponding clipping value, a chroma table (e.g., used for achroma CB) of the clipping value index and the corresponding clippingvalue. The clipping value can be dependent of a bit depth B. The bitdepth B can refer to an internal bit depth, a bit depth of reconstructedsamples in a CB to be filtered, or the like. In some examples, a table(e.g., a luma table, a chroma table) is obtained using Eq. (12).

$\begin{matrix}{{{AlfClip} = \{ {{{{round}( 2^{B\;\frac{N - n + 1}{N}} )}\mspace{14mu}{for}\mspace{14mu} n} \in \lbrack {1\mspace{14mu}\ldots\mspace{14mu} N} \rbrack} \}},} & {{Eq}.\mspace{14mu}(12)}\end{matrix}$where AlfClip is the clipping value, B is the bit depth (e.g.,bitDepth), N (e.g., N=4) is a number of allowed clipping values, and(n−1) is the clipping value index (also referred to as clipping index orclipIdx). Table 2 shows an example of a table obtained using Eq. (12)with N=4. The clipping index (n−1) can be 0, 1, 2, and 3 in Table 2, andn can be 1, 2, 3, and 4, respectively. Table 2 can be used for lumablocks or chroma blocks.

TABLE 2 AlfClip can depend on the bit depth B and clipIdx clipIdxbitDepth 0 1 2 3 8 255 64 16 4 9 511 108 23 5 10 1023 181 32 6 11 2047304 45 7 12 4095 512 64 8 13 8191 861 91 10 14 16383 1448 128 11 1532767 2435 181 13 16 65535 4096 256 16

In a slice header for a current slice, one or more APS indices (e.g., upto 7 APS indices) can be signaled to specify luma filter sets that canbe used for the current slice. The filtering process can be controlledat one or more suitable levels, such as a picture level, a slice level,a CTB level, and/or the like. In an embodiment, the filtering processcan be further controlled at a CTB level. A flag can be signaled toindicate whether the ALF is applied to a luma CTB. The luma CTB canchoose a filter set among a plurality of fixed filter sets (e.g., 16fixed filter sets) and the filter set(s) (also referred to as signaledfilter set(s)) that are signaled in the APSs. A filter set index can besignaled for the luma CTB to indicate the filter set (e.g., the filterset among the plurality of fixed filter sets and the signaled filterset(s)) to be applied. The plurality of fixed filter sets can bepre-defined and hard-coded in an encoder and a decoder, and can bereferred to as pre-defined filter sets.

For a chroma component, an APS index can be signaled in the slice headerto indicate the chroma filter sets to be used for the current slice. Atthe CTB level, a filter set index can be signaled for each chroma CTB ifthere is more than one chroma filter set in the APS.

The filter coefficients can be quantized with a norm equal to 128. Inorder to decrease the multiplication complexity, a bitstream conformancecan be applied so that the coefficient value of the non-central positioncan be in a range of −27 to 27−1, inclusive. In an example, the centralposition coefficient is not signaled in the bitstream and can beconsidered as equal to 128.

In some embodiments, the syntaxes and semantics of clipping index andclipping values are defined as follows:

alf_luma_clip_idx[sfIdx][j] can be used to specify the clipping index ofthe clipping value to use before multiplying by the j-th coefficient ofthe signaled luma filter indicated by sfIdx. A requirement of bitstreamconformance can include that the values of alf_luma_clip_idx[sfIdx][j]with sfIdx=0 to alf_luma_num_filters_signalled_minus1 and j=0 to 11shall be in the range of 0 to 3, inclusive.The luma filter clipping values AlfClipL[adaptation_parameter_set_id]with elements AlfClipL[adaptation_parameter_set_id][filtIdx][j], withfiltIdx=0 to NumAlfFilters−1 and j=0 to 11 can be derived as specifiedin Table 2 depending on bitDepth set equal to BitDepthY and clipIdx setequal to alf_luma_clip_idx[alf_luma_coeff_delta_idx[filtIdx] ][j].alf_chroma_clip_idx[altIdx][j] can be used to specify the clipping indexof the clipping value to use before multiplying by the j-th coefficientof the alternative chroma filter with index altIdx. A requirement ofbitstream conformance can include that the values ofalf_chroma_clip_idx[altIdx][j] with altIdx=0 toalf_chroma_num_alt_filters_minus1, j=0 to 5 shall be in the range of 0to 3, inclusive.The chroma filter clipping valuesAlfClipC[adaptation_parameter_set_id][altIdx] with elementsAlfClipC[adaptation_parameter_set_id][altIdx][j], with altIdx=0 toalf_chroma_num_alt_filters_minus1, j=0 to 5 can be derived as specifiedin Table 2 depending on bitDepth set equal to BitDepthC and clipIdx setequal to alf_chroma_clip_idx[altIdx][j].

In an embodiment, the filtering process can be described as below. At adecoder side, when the ALF is enabled for a CTB, a sample R(i,j) withina CU (or CB) can be filtered, resulting in a filtered sample valueR′(i,j) as shown below using Eq. (13). In an example, each sample in theCU is filtered.

$\begin{matrix}{{R^{\prime}( {i,j} )} = {{R( {i,j} )} + ( {( {{\sum\limits_{k \neq 0}{\sum\limits_{l \neq 0}{{f( {k,l} )} \times {K( {{{R( {{i + k},{j + l}} )} - {R( {i,j} )}},{c( {k,l} )}} )}}}} + 64} )\operatorname{>>}7} )}} & {{Eq}.\mspace{14mu}(13)}\end{matrix}$where f(k,l) denotes the decoded filter coefficients, K(x, y) is aclipping function, and c(k, l) denotes the decoded clipping parameters(or clipping values). The variables k and l can vary between −L/2 andL/2 where L denotes a filter length. The clipping function K(x, y)=min(y, max(−y, x)) corresponds to a clipping function Clip3 (−y, y, x). Byincorporating the clipping function K(x, y), the loop filtering method(e.g., ALF) becomes a non-linear process, and can be referred to anonlinear ALF.

In the nonlinear ALF, multiple sets of clipping values can be providedin Table 3. In an example, a luma set includes four clipping values{1024, 181, 32, 6}, and a chroma set includes 4 clipping values {1024,161, 25, 4}. The four clipping values in the luma set can be selected byapproximately equally splitting, in a logarithmic domain, a full range(e.g., 1024) of the sample values (coded on 10 bits) for a luma block.The range can be from 4 to 1024 for the chroma set.

TABLE 3 Examples of clipping values INTRA/INTER tile group LUMA { 1024,181, 32, 6 } CHROMA { 1024, 161, 25, 4 }

The selected clipping values can be coded in an “alf_data” syntaxelement as follows: a suitable encoding scheme (e.g., a Golomb encodingscheme) can be used to encode a clipping index corresponding to theselected clipping value such as shown in Table 3. The encoding schemecan be the same encoding scheme used for encoding the filter set index.

In an embodiment, a virtual boundary filtering process can be used toreduce a line buffer requirement of the ALF. Accordingly, modified blockclassification and filtering can be employed for samples near CTUboundaries (e.g., a horizontal CTU boundary). A virtual boundary (1130)can be defined as a line by shifting a horizontal CTU boundary (1120) by“N_(samples)” samples, as shown in FIG. 11A, where N_(samples) can be apositive integer. In an example, N_(samples) is equal to 4 for a lumacomponent, and N_(samples) is equal to 2 for a chroma component.

Referring to FIG. 11A, a modified block classification can be appliedfor a luma component. In an example, for the 1D Laplacian gradientcalculation of a 4×4 block (1110) above the virtual boundary (1130),only samples above the virtual boundary (1130) are used. Similarly,referring to FIG. 11B, for a 1D Laplacian gradient calculation of a 4×4block (1111) below a virtual boundary (1131) that is shifted from a CTUboundary (1121), only samples below the virtual boundary (1131) areused. The quantization of an activity value A can be accordingly scaledby taking into account a reduced number of samples used in the 1DLaplacian gradient calculation.

For a filtering processing, a symmetric padding operation at virtualboundaries can be used for both a luma component and a chroma component.FIGS. 12A-12F illustrate examples of such modified ALF filtering for aluma component at virtual boundaries. When a sample being filtered islocated below a virtual boundary, neighboring samples that are locatedabove the virtual boundary can be padded. When a sample being filteredis located above a virtual boundary, neighboring samples that arelocated below the virtual boundary can be padded. Referring to FIG. 12A,a neighboring sample C0 can be padded with a sample C2 that is locatedbelow a virtual boundary (1210). Referring to FIG. 12B, a neighboringsample C0 can be padded with a sample C2 that is located above a virtualboundary (1220). Referring to FIG. 12C, neighboring samples C1-C3 can bepadded with samples C5-C7, respectively, that are located below avirtual boundary (1230). Referring to FIG. 12D, neighboring samplesC1-C3 can be padded with samples C5-C7, respectively, that are locatedabove a virtual boundary (1240). Referring to FIG. 12E, neighboringsamples C4-C8 can be padded with samples C10, C11, C12, C11, and C10,respectively, that are located below a virtual boundary (1250).Referring to FIG. 12F, neighboring samples C4-C8 can be padded withsamples C10, C11, C12, C11, and C10, respectively, that are locatedabove a virtual boundary (1260).

In some examples, the above description can be suitably adapted whensample(s) and neighboring sample(s) are located to the left (or to theright) and to the right (or to the left) of a virtual boundary.

According to an aspect of the disclosure, in order to improve codingefficiency, pictures can be partitioned based on filtering process. Insome examples, a CTU is also referred to as a largest coding unit (LCU).In an example, the CTU or LCU can have a size of 64×64 pixels. In someembodiments, LCU-Aligned picture quadtree splitting can be used for thefiltering based partition. In some examples, the coding unit synchronouspicture quadtree-based adaptive loop filter can be used. For example,the luma picture can be split into several multi-level quadtreepartitions, and each partition boundary is aligned to the boundaries ofthe LCUs. Each partition has its own filtering process and thus bereferred to as a filter unit (FU).

In some examples, a 2-pass encoding flow can be used. At a first pass ofthe 2-pass encoding flow, the quadtree split pattern of the picture andthe best filter of each FU can be determined. In some embodiment, thedetermination of the quadtree split pattern of the picture and thedetermination of the best filters for FUs are based on filteringdistortions. The filtering distortions can be estimated by fastfiltering distortion estimation (FFDE) technique during thedetermination process. The picture is partitioned using quadtreepartition. According to the determined quadtree split pattern and theselected filters of all FUs, the reconstructed picture can be filtered.

At a second pass of the 2-pass encoding flow, the CU synchronous ALFon/off control is performed. According to the ALF on/off results, thefirst filtered picture is partially recovered by the reconstructedpicture.

Specifically, in some examples, a top-down splitting strategy is adoptedto divide a picture into multi-level quadtree partitions by using arate-distortion criterion. Each partition is called a filter unit (FU).The splitting process aligns quadtree partitions with LCU boundaries.The encoding order of FUs follows the z-scan order.

FIG. 13 shows a partition example according to some embodiments of thedisclosure. In the FIG. 13 example, a picture (1300) is split into 10FUs, and the encoding order is FU0, FU1, FU2, FU3, FU4, FU5, FU6, FU7,FU8, and FU9.

FIG. 14 shows a quadtree split pattern (1400) for the picture (1300). Inthe FIG. 14 example, split flags are used to indicate the picturepartition pattern. For example, “1” indicates a quadtree partition isperformed on the block; and “0” indicates that the block is not furtherpartitioned. In some examples, a minimum size FU has the LCU size, andno split flag is needed for the minimum size FU. The split flags areencoded and transmitted in z-order as shown in FIG. 14 .

In some examples, the filter of each FU is selected from two filter setsbased on the rate-distortion criterion. The first set has ½-symmetricsquare-shaped and rhombus-shaped filters derived for the current FU. Thesecond set comes from time-delayed filter buffers; the time-delayedfilter buffers store the filters previously derived for FUs of priorpictures. The filter with the minimum rate-distortion cost of these twosets can be chosen for the current FU. Similarly, if the current FU isnot the smallest FU and can be further split into 4 children FUs, therate-distortion costs of the 4 children FUs are calculated. By comparingthe rate-distortion cost of the split and non-split cases recursively,the picture quadtree split pattern can be decided.

In some examples, a maximum quadtree split level may be used to limitthe maximum number of FUs. In an example, when the maximum quadtreesplit level is 2, the maximum number of FUs is 16. Further, during thequadtree split determination, the correlation values for deriving Wienercoefficients of the 16 FUs at the bottom quadtree level (smallest FUs)can be reused. The rest FUs can derive their Wiener filters from thecorrelations of the 16 FUs at the bottom quadtree level. Therefore, inthe example, only one frame buffer access is performed for deriving thefilter coefficients of all FUs.

After the quadtree split pattern is decided, to further reduce thefiltering distortion, the CU synchronous ALF on/off control can beperformed. By comparing the filtering distortion and non-filteringdistortion at each leaf CU, the leaf CU can explicitly switch ALF on/offin its local region. In some examples, the coding efficiency may befurther improved by redesigning the filter coefficients according to theALF on/off results.

A cross-component filtering process can apply cross-component filters,such as cross-component adaptive loop filters (CC-ALFs). Thecross-component filter can use luma sample values of a luma component(e.g., a luma CB) to refine a chroma component (e.g., a chroma CBcorresponding to the luma CB). In an example, the luma CB and the chromaCB are included in a CU.

FIG. 15 shows cross-component filters (e.g., CC-ALFs) used to generatechroma components according to an embodiment of the disclosure. In someexamples, FIG. 15 shows filtering processes for a first chroma component(e.g., a first chroma CB), a second chroma component (e.g., a secondchroma CB), and a luma component (e.g., a luma CB). The luma componentcan be filtered by a sample adaptive offset (SAO) filter (1510) togenerate a SAO filtered luma component (1541). The SAO filtered lumacomponent (1541) can be further filtered by an ALF luma filter (1516) tobecome a filtered luma CB (1561) (e.g., ‘Y’).

The first chroma component can be filtered by a SAO filter (1512) and anALF chroma filter (1518) to generate a first intermediate component(1552). Further, the SAO filtered luma component (1541) can be filteredby a cross-component filter (e.g., CC-ALF) (1521) for the first chromacomponent to generate a second intermediate component (1542).Subsequently, a filtered first chroma component (1562) (e.g., ‘Cb’) canbe generated based on at least one of the second intermediate component(1542) and the first intermediate component (1552). In an example, thefiltered first chroma component (1562) (e.g., ‘Cb’) can be generated bycombining the second intermediate component (1542) and the firstintermediate component (1552) with an adder (1522). The cross-componentadaptive loop filtering process for the first chroma component caninclude a step performed by the CC-ALF (1521) and a step performed by,for example, the adder (1522).

The above description can be adapted to the second chroma component. Thesecond chroma component can be filtered by a SAO filter (1514) and theALF chroma filter (1518) to generate a third intermediate component(1553). Further, the SAO filtered luma component (1541) can be filteredby a cross-component filter (e.g., a CC-ALF) (1531) for the secondchroma component to generate a fourth intermediate component (1543).Subsequently, a filtered second chroma component (1563) (e.g., ‘Cr’) canbe generated based on at least one of the fourth intermediate component(1543) and the third intermediate component (1553). In an example, thefiltered second chroma component (1563) (e.g., ‘Cr’) can be generated bycombining the fourth intermediate component (1543) and the thirdintermediate component (1553) with an adder (1532). In an example, thecross-component adaptive loop filtering process for the second chromacomponent can include a step performed by the CC-ALF (1531) and a stepperformed by, for example, the adder (1532).

A cross-component filter (e.g., the CC-ALF (1521), the CC-ALF (1531))can operate by applying a linear filter having any suitable filter shapeto the luma component (or a luma channel) to refine each chromacomponent (e.g., the first chroma component, the second chromacomponent).

FIG. 16 shows an example of a filter (1600) according to an embodimentof the disclosure. The filter (1600) can include non-zero filtercoefficients and zero filter coefficients. The filter (1600) has adiamond shape (1620) formed by filter coefficients (1610) (indicated bycircles having black fill). In an example, the non-zero filtercoefficients in the filter (1600) are included in the filtercoefficients (1610), and filter coefficients not included in the filtercoefficients (1610) are zero. Thus, the non-zero filter coefficients inthe filter (1600) are included in the diamond shape (1620), and thefilter coefficients not included in the diamond shape (1620) are zero.In an example, a number of the filter coefficients of the filter (1600)is equal to a number of the filter coefficients (1610), which is 18 inthe example shown in FIG. 16 .

The CC-ALF can include any suitable filter coefficients (also referredto as the CC-ALF filter coefficients). Referring back to FIG. 15 , theCC-ALF (1521) and the CC-ALF (1531) can have a same filter shape, suchas the diamond shape (1620) shown in FIG. 16 , and a same number offilter coefficients. In an example, values of the filter coefficients inthe CC-ALF (1521) are different from values of the filter coefficientsin the CC-ALF (1531).

In general, filter coefficients (e.g., non-zero filter coefficients) ina CC-ALF can be transmitted, for example, in the APS. In an example, thefilter coefficients can be scaled by a factor (e.g., 2¹⁰) and can berounded for a fixed point representation. Application of a CC-ALF can becontrolled on a variable block size and signaled by a context-coded flag(e.g., a CC-ALF enabling flag) received for each block of samples. Thecontext-coded flag, such as the CC-ALF enabling flag, can be signaled atany suitable level, such as a block level. The block size along with theCC-ALF enabling flag can be received at a slice-level for each chromacomponent. In some examples, block sizes (in chroma samples) 16×16,32×32, and 64×64 can be supported.

FIG. 17 shows a syntax example for CC-ALF according to some embodimentsof the disclosure. In the FIG. 17 example,

alf_ctb_cross_component_cb_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY]is an index to indicate whether a cross component Cb filter is used andan index of the cross component Cb filter if used. For example, when

alf_ctb_cross_component_cb_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY]is equal to 0, the cross component Cb filter is not applied to block ofCb colour component samples at luma location (xCtb, yCtb); when

alf_ctb_cross_component_cb_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY]is not equal to 0,

alf_ctb_cross_component_cb_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY]is an index for a filter to be applied. For example,

alf_ctb_cross_component_cb_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY]-thcross component Cb filter is applied to the block of Cb colour componentsamples at luma location (xCtb, yCtb)

Further, in the FIG. 17 example,

alf_ctb_cross_component_cr_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY]is used to indicate whether a cross component Cr filter is used andindex of the cross component Cr filter is used. For example, when

alf_ctb_cross_component_cr_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY]is equal to 0, the cross component Cr filter is not applied to block ofCr colour component samples at luma location (xCtb, yCtb); when

alf_ctb_cross_component_cr_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY]is not equal to 0,

alf_ctb_cross_component_cr_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY]is the index of the cross component Cr filter. For example,

alf_cross_component_cr_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY]-thcross component Cr filter can be applied to the block of Cr colourcomponent samples at luma location (xCtb, yCtb)

In some examples, chroma subsampling techniques are used, thus a numberof samples in each of the chroma block(s) can be less than a number ofsamples in the luma block. A chroma subsampling format (also referred toas a chroma subsampling format, e.g., specified by chroma_format_idc)can indicate a chroma horizontal subsampling factor (e.g., SubWidthC)and a chroma vertical subsampling factor (e.g., SubHeightC) between eachof the chroma block(s) and the corresponding luma block. In an example,the chroma subsampling format is 4:2:0, and thus the chroma horizontalsubsampling factor (e.g., SubWidthC) and the chroma vertical subsamplingfactor (e.g., SubHeightC) are 2, as shown in FIGS. 18A-18B. In anexample, the chroma subsampling format is 4:2:2, and thus the chromahorizontal subsampling factor (e.g., SubWidthC) is 2, and the chromavertical subsampling factor (e.g., SubHeightC) is 1. In an example, thechroma subsampling format is 4:4:4, and thus the chroma horizontalsubsampling factor (e.g., SubWidthC) and the chroma vertical subsamplingfactor (e.g., SubHeightC) are 1. A chroma sample type (also referred toas a chroma sample position) can indicate a relative position of achroma sample in the chroma block with respect to at least onecorresponding luma sample in the luma block.

FIGS. 18A-18B show exemplary locations of chroma samples relative toluma samples according to embodiments of the disclosure. Referring toFIG. 18A, the luma samples (1801) are located in rows (1811)-(1818). Theluma samples (1801) shown in FIG. 18A can represent a portion of apicture. In an example, a luma block (e.g., a luma CB) includes the lumasamples (1801). The luma block can correspond to two chroma blockshaving the chroma subsampling format of 4:2:0. In an example, eachchroma block includes chroma samples (1803). Each chroma sample (e.g.,the chroma sample (1803(1)) corresponds to four luma samples (e.g., theluma samples (1801(1))-(1801(4)). In an example, the four luma samplesare the top-left sample (1801(1)), the top-right sample (1801(2)), thebottom-left sample (1801(3)), and the bottom-right sample (1801(4)). Thechroma sample (e.g., (1803(1))) is located at a left center positionthat is between the top-left sample (1801(1)) and the bottom-left sample(1801(3)), and a chroma sample type of the chroma block having thechroma samples (1803) can be referred to as a chroma sample type 0. Thechroma sample type 0 indicates a relative position 0 corresponding tothe left center position in the middle of the top-left sample (1801(1))and the bottom-left sample (1801(3)). The four luma samples (e.g.,(1801(1))-(1801(4))) can be referred to as neighboring luma samples ofthe chroma sample (1803)(1).

In an example, each chroma block includes chroma samples (1804). Theabove description with reference to the chroma samples (1803) can beadapted to the chroma samples (1804), and thus detailed descriptions canbe omitted for purposes of brevity. Each of the chroma samples (1804)can be located at a center position of four corresponding luma samples,and a chroma sample type of the chroma block having the chroma samples(1804) can be referred to as a chroma sample type 1. The chroma sampletype 1 indicates a relative position 1 corresponding to the centerposition of the four luma samples (e.g., (1801(1))-(1801(4))). Forexample, one of the chroma samples (1804) can be located at a centerportion of the luma samples (1801(1))-(1801(4)).

In an example, each chroma block includes chroma samples (1805). Each ofthe chroma samples (1805) can be located at a top left position that isco-located with the top-left sample of the four corresponding lumasamples (1801), and a chroma sample type of the chroma block having thechroma samples (1805) can be referred to as a chroma sample type 2.Accordingly, each of the chroma samples (1805) is co-located with thetop left sample of the four luma samples (1801) corresponding to therespective chroma sample. The chroma sample type 2 indicates a relativeposition 2 corresponding to the top left position of the four lumasamples (1801). For example, one of the chroma samples (1805) can belocated at a top left position of the luma samples (1801(1))-(1801(4)).

In an example, each chroma block includes chroma samples (1806). Each ofthe chroma samples (1806) can be located at a top center positionbetween a corresponding top-left sample and a corresponding top-rightsample, and a chroma sample type of the chroma block having the chromasamples (1806) can be referred to as a chroma sample type 3. The chromasample type 3 indicates a relative position 3 corresponding to the topcenter position between the top-left sample (and the top-right sample.For example, one of the chroma samples (1806) can be located at a topcenter position of the luma samples (1801(1))-(1801(4)).

In an example, each chroma block includes chroma samples (1807). Each ofthe chroma samples (1807) can be located at a bottom left position thatis co-located with the bottom-left sample of the four corresponding lumasamples (1801), and a chroma sample type of the chroma block having thechroma samples (1807) can be referred to as a chroma sample type 4.Accordingly, each of the chroma samples (1807) is co-located with thebottom left sample of the four luma samples (1801) corresponding to therespective chroma sample. The chroma sample type 4 indicates a relativeposition 4 corresponding to the bottom left position of the four lumasamples (1801). For example, one of the chroma samples (1807) can belocated at a bottom left position of the luma samples(1801(1))-(1801(4)).

In an example, each chroma block includes chroma samples (1808). Each ofthe chroma samples (1808) is located at a bottom center position betweenthe bottom-left sample and the bottom-right sample, and a chroma sampletype of the chroma block having the chroma samples (1808) can bereferred to as a chroma sample type 5. The chroma sample type 5indicates a relative position 5 corresponding to the bottom centerposition between the bottom-left sample and the bottom-right sample ofthe four luma samples (1801). For example, one of the chroma samples(1808) can be located between the bottom-left sample and thebottom-right sample of the luma samples (1801(1))-(1801(4)).

In general, any suitable chroma sample type can be used for a chromasubsampling format. The chroma sample types 0-5 are exemplary chromasample types described with the chroma subsampling format 4:2:0.Additional chroma sample types may be used for the chroma subsamplingformat 4:2:0. Further, other chroma sample types and/or variations ofthe chroma sample types 0-5 can be used for other chroma subsamplingformats, such as 4:2:2, 4:4:4, or the like. In an example, a chromasample type combining the chroma samples (1805) and (1807) is used forthe chroma subsampling format 4:2:2.

In an example, the luma block is considered to have alternating rows,such as the rows (1811)-(1812) that include the top two samples (e.g.,(1801(1))-(180)(2))) of the four luma samples (e.g.,(1801(1))-(1801(4))) and the bottom two samples (e.g.,(1801(3))-(1801(4))) of the four luma samples (e.g.,(1801(1)-(1801(4))), respectively. Accordingly, the rows (1811), (1813),(1815), and (1817) can be referred to as current rows (also referred toas a top field), and the rows (1812), (1814), (1816), and (1818) can bereferred to as next rows (also referred to as a bottom field). The fourluma samples (e.g., (1801(1))-(1801(4))) are located at the current row(e.g., (1811)) and the next row (e.g., (1812)). The relative positions2-3 are located in the current rows, the relative positions 0-1 arelocated between each current row and the respective next row, and therelative positions 4-5 are located in the next rows.

The chroma samples (1803), (1804), (1805), (1806), (1807), or (1808) arelocated in rows (1851)-(1854) in each chroma block. Specific locationsof the rows (1851)-(1854) can depend on the chroma sample type of thechroma samples. For example, for the chroma samples (1803)-(1804) havingthe respective chroma sample types 0-1, the row (1851) is locatedbetween the rows (1811)-(1812). For the chroma samples (1805)-(1806)having the respective the chroma sample types 2-3, the row (1851) isco-located with the current row (1811). For the chroma samples(1807)-(1808) having the respective the chroma sample types 4-5, the row(1851) is co-located with the next row (1812). The above descriptionscan be suitably adapted to the rows (1852)-(1854), and the detaileddescriptions are omitted for purposes of brevity.

Any suitable scanning method can be used for displaying, storing, and/ortransmitting the luma block and the corresponding chroma block(s)described above in FIG. 18A. In an example, progressive scanning isused.

An interlaced scan can be used, as shown in FIG. 18B. As describedabove, the chroma subsampling format is 4:2:0 (e.g., chroma_format_idcis equal to 1). In an example, a variable chroma location type (e.g.,ChromaLocType) indicates the current rows (e.g., ChromaLocType ischroma_sample_loc_type_top_field) or the next rows (e.g., ChromaLocTypeis chroma_sample_loc_type_bottom_field). The current rows (1811),(1813), (1815), and (1817) and the next rows (1812), (1814), (1816), and(1818) can be scanned separately, for example, the current rows (1811),(1813), (1815), and (1817) can be scanned first followed by the nextrows (1812), (1814), (1816), and (1818) being scanned. The current rowscan include the luma samples (1801) while the next rows can include theluma samples (1802).

Similarly, the corresponding chroma block can be interlaced scanned. Therows (1851) and (1853) including the chroma samples (1803), (1804),(1805), (1806), (1807), or (1808) with no fill can be referred to ascurrent rows (or current chroma rows), and the rows (1852) and (1854)including the chroma samples (1803), (1804), (1805), (1806), (1807), or(1808) with gray fill can be referred to as next rows (or next chromarows). In an example, during the interlaced scan, the rows (1851) and(1853) are scanned first followed by scanning the rows (1852) and(1854).

In some examples, constrained directional enhancement filteringtechniques can be used. The use of an in-loop constrained directionalenhancement filter (CDEF) can filter out coding artifacts whileretaining the details of the image. In an example (e.g., HEVC), sampleadaptive offset (SAO) algorithm can achieves a similar goal by definingsignal offsets for different classes of pixels. Unlike SAO, CDEF is anon-linear spatial filter. In some examples, CDEF can be constrained tobe easily vectorizable (i.e. implementable with single instructionmultiple data (SIMD) operations). It is noted that other non-linearfilters, such as a median filter, a bilateral filter cannot be handledin the same manner.

In some cases, the amount of ringing artifacts in a coded image tends tobe roughly proportional to the quantization step size. The amount ofdetail is a property of the input image, but the smallest detailretained in the quantized image tends to also be proportional to thequantization step size. For a given quantization step size, theamplitude of the ringing is generally less than the amplitude of thedetails.

CDEF can be used to identify the direction of each block and thenadaptively filter along the identified direction and filter to a lesserdegree along directions rotated 45 degrees from the identifieddirection. In some examples, an encoder can search for the filterstrengths and the filter strengths can be signaled explicitly, whichallows a high degree of control over the blurring.

Specifically, in some examples, the direction search is performed on thereconstructed pixels, just after the deblocking filter. Since thosepixels are available to the decoder, the directions can be searched bythe decoder, and thus the directions require no signaling in an example.In some examples, the direction search can operate on certain blocksize, such 8×8 blocks, which are small enough to adequately handlenon-straight edges, while being large enough to reliably estimatedirections when applied to a quantized image. Also, having a constantdirection over an 8×8 region makes vectorization of the filter easier.In some examples, each block (e.g., 8×8) can be compared to perfectlydirectional blocks to determine difference. A perfectly directionalblock is a block where all of the pixels along a line in one directionhave the same value. In an example, a difference measure of the blockand each of the perfectly directional blocks, such as sum of squareddifferences (SSD), root mean square (RMS) error can be calculated. Then,a perfectly directional block with minimum difference (e.g., minimumSSD, minimum RMS, and the like) can be determined and the direction ofthe determined perfectly directional block can be is direction that bestmatches the pattern in the block.

FIG. 19 shows an example of direction search according to an embodimentof the disclosure. In an example, a block (1910) is an 8×8 block that isreconstructed, and output from a deblocking filter. In the FIG. 19example, the direction search can determine a direction from 8directions shown by (1920) for the block (1910). 8 perfectly directionalblocks (1930) are formed respectively corresponding to the 8 directions(1920). A perfectly directional block corresponding to a direction is ablock where pixels along a line of the direction have the same value.Further, a difference measure, such as SSD, RMS error and the like, ofthe block (1910) and each of the perfectly directional blocks (1930) canbe calculated. In the FIG. 19 example, the RMS errors are shown by(1940). As shown by (1943), the RMS error of the block (1910) and theperfectly directional block (1933) is the smallest, thus the direction(1923) is the direction that best matches the pattern in the block(1910).

After the direction of the block is identified, a non-linear low passdirectional filter can be determined. For example, the filter taps ofthe non-linear low pass directional filter can be aligned along theidentified direction to reduce ringing while preserving the directionaledges or patterns. However, in some examples, directional filteringalone sometimes cannot sufficiently reduce ringing. In an example, extrafilter taps are also used on pixels that do not lie along the identifieddirection. To reduce the risk of blurring, the extra filter taps aretreated more conservatively. For this reason, CDEF includes primaryfilter taps and secondary filter taps. In an example, a complete 2-DCDEF filter can be expressed as Eq. (14):

$\begin{matrix}{{{y( {i,j} )} = {{x( {i,j} )} + {{round}( {{\sum\limits_{m,n}{w_{d,m,n}^{(p)}{f( {{{x( {m,n} )} - {x( {i,j} )}},S^{(p)},D} )}}} + {\sum\limits_{m,n}{w_{d,m,n}^{(s)}{f( {{{x( {m,n} )} - {x( {i,j} )}},S^{(b)},D} )}}}} )}}},} & {{Eq}.\mspace{14mu}(14)}\end{matrix}$where D denotes a damping parameter, S^((p)) denotes the strength of theprimary filter taps, S^((s)) denotes the strength of the secondaryfilter taps, round(⋅) denotes an operation that rounds ties away fromzero, w denote the filter weights and ƒ(d, S, D) is a constraintfunction operating on the difference between the filtered pixel and eachof the neighboring pixels. In an example, for small differences, thefunction ƒ(d, S, D) is equal to D, that can make the filter to behavelike a linear filter; when the difference is large, the function ƒ(d, S,D) is equal to 0, that can effectively ignores the filter taps.

In some examples, in-loop restoration schemes are used in video codingpost deblocking to generally denoise and enhance the quality of edges,beyond the deblocking operation. In an example, the in-loop restorationschemes are switchable within a frame per suitably sized tile. Thein-loop restoration schemes are based on separable symmetric Wienerfilters, dual self-guided filters with subspace projection, and domaintransform recursive filters. Because content statistics can varysubstantially within a frame, in-loop restoration schemes are integratedwithin a switchable framework where different schemes can be triggeredin different regions of the frame.

Separable symmetric Wiener filter can be one of the in-loop restorationschemes. In some examples, every pixel in a degraded frame can bereconstructed as a non-causal filtered version of the pixels within aw×w window around it where w=2r+1 is odd for integer r. If the 2D filtertaps are denoted by a w²×1 element vector F in column-vectorized form, astraightforward LMMSE optimization leads to filter parameters beinggiven by F=H⁻¹ M, where H=E[XX^(T)] is the autocovariance of x, thecolumn-vectorized version of the w² samples in the w×w window around apixel, and M=E[YX^(T)] is the cross correlation of x with the scalarsource sample y, to be estimated. In an example, the encoder canestimate H and M from realizations in the deblocked frame and the sourceand can send the resultant filter F to the decoder. However, that wouldnot only incur a substantial bit rate cost in transmitting w² taps, butalso non-separable filtering will make decoding prohibitively complex.In some embodiments, several additional constraints are imposed on thenature of F. For the first constraint, F is constrained to be separableso that the filtering can be implemented as separable horizontal andvertical w-tap convolutions. For the second constraint, each of thehorizontal and vertical filters are constrained to be symmetric. For thethird constraint, the sum of both the horizontal and vertical filtercoefficients is assumed to sum to 1.

Dual self-guided filtering with subspace projection can be one of thein-loop restoration schemes. Guided filtering is an image filteringtechnique where a local linear model shown by Eq. (15):y=Fx+G  Eq. (15)is used to compute the filtered output y from an unfiltered sample x,where F and G are determined based on the statistics of the degradedimage and a guidance image in the neighborhood of the filtered pixel. Ifthe guide image is the same as the degraded image, the resultantso-called self-guided filtering has the effect of edge preservingsmoothing. In an example, a specific form of self-guided filtering canbe used. The specific form of self-guided filtering depends on twoparameters: a radius r and a noise parameter e, and is enumerated asfollows steps:

-   -   1. Obtain mean μ and variance σ² of pixels in a (2r+1)×(2r+1)        window around every pixel. This step can be implemented        efficiently with box filtering based on integral imaging.    -   2. Compute for every pixel: f=σ²/(σ²+e); g=(1−f)μ    -   3. Compute F and G for every pixel as averages of f and g values        in a 3×3 window around the pixel for use.

The specific form of self-guided filter is controlled by r and e, wherea higher r implies a higher spatial variance and a higher e implies ahigher range variance.

FIG. 20 shows an example illustrating subspace projection in someexamples. As shown in FIG. 20 , even though none of the restorations X₁,X₂ are close to the source Y, appropriate multipliers {α,β} can bringthem much closer to the source Y as long as they are moving somewhat inthe right direction.

In some examples (e.g., HEVC), a filtering technique that is referred toas sample adaptive offset (SAO) can be used. In some examples, SAO isapplied to the reconstruction signal after a deblocking filter. SAO canuse the offset values given in the slice header. In some examples, forluma samples, the encoder can decide whether to apply (enable) SAO on aslice. When SAO is enabled, the current picture allows recursivesplitting of a coding unit into four sub-regions and each sub-region canselect an SAO type from multiple SAO types based on features in thesub-region.

FIG. 21 shows a table (2100) of a plurality of SAO types according to anembodiment of the disclosure. In the table (2100), SAO types 0-6 areshown. It is noted that SAO type 0 is used to indicate no SAOapplication. Further, each SAO type of SAO type 1 to SAO type 6 includesmultiple categories. SAO can classify reconstructed pixels of asub-region into categories and reduce the distortion by adding an offsetto pixels of each category in the sub-region. In some examples, edgeproperties can be used for pixel classification in SAO types 1-4, andpixel intensity can be used for pixel classification in SAO types 5-6.

Specifically, in an embodiment, such as SAO types 5-6, band offset (BO)can be used to classify all pixels of a sub-region into multiple bands.Each band of the multiple bands includes pixels in the same intensityinterval. In some examples, the intensity range is equally divided intoa plurality of intervals, such as 32 intervals from zero to the maximumintensity value (e.g. 255 for 8-bit pixels), and each interval isassociated with an offset. Further, in an example, the 32 bands aredivided into two groups, such as a first group and a second group. Thefirst group includes the central 16 bands (e.g., 16 intervals that arein the middle of the intensity range), while the second group includesof the rest 16 bands (e.g., 8 intervals that are at the low side of theintensity range and 8 intervals that are at the high side of theintensity range). In an example, only offsets of one of the two groupsare transmitted. In some embodiments, when the pixel classificationoperation in BO is used, the five most significant bits of each pixelcan be directly used as the band index.

Further, in an embodiment, such as SAO types 1-4, edge offset (EO) canbe used for pixel classification and determination of offsets. Forexample, pixel classification can be determined based on 1-dimensional3-pixel patterns with consideration of edge directional information.

FIG. 22 shows examples of 3-pixel patterns for pixel classification inedge offset in some examples. In the FIG. 22 example, a first pattern(2210) (as shown by 3 grey pixels) is referred to as 0-degree pattern(horizontal direction is associated with the 0-degree pattern), a secondpattern (2220) (as shown by 3 grey pixels) is referred to as 90-degreepattern (vertical direction is associated with the 90-degree pattern), athird pattern (2230) (as shown by 3 grey pixels) is referred to as135-degree pattern (135 degree diagonal direction is associated with the135-degree pattern) and a fourth pattern (2240) (as shown by 3 greypixels) is referred to as 45-degree pattern (45 degree diagonaldirection is associated with the 45-degree pattern). In an example, oneof the four directional patterns shown in FIG. 22 can be selectedconsidering edge directional information for a sub-region. The selectioncan be sent in the coded video bitstream as side information in anexample. Then, pixels in the sub-region can be classified into multiplecategories by comparing each pixel with its two neighboring pixels onthe direction associated with the directional pattern.

FIG. 23 shows a table (2300) for pixel classification rule for edgeoffset in some examples. Specifically, a pixel c (also shown in eachpattern of FIG. 22 ) is compared with two neighboring pixels (also shownby grey color in each pattern of FIG. 22 ), and the pixel c can beclassified into one of category 0-4 based on the comparison according tothe pixel classification rule shown in FIG. 23 .

In some embodiments, the SAO on the decoder side can be operatedindependently of largest coding unit (LCU) (e.g., CTU), so that the linebuffers can be saved. In some examples, pixels of the top and bottomrows in each LCU are not SAO processed when the 90-degree, 135-degree,and 45-degree classification patterns are chosen; pixels of the leftmostand rightmost columns in each LCU are not SAO processed when the0-degree, 135-degree, and 45-degree patterns are chosen.

FIG. 24 shows an example (2400) of syntaxes that may need to be signaledfor a CTU if the parameters are not merged from neighboring CTU. Forexample, a syntax element sao_type_idx[cldx][rx][ry] can be signaled toindicate the SAO type of a sub-region. The SAO type may be BO (bandoffset) or EO (edge offset). When sao_type_idx[cldx][rx][ry] has a valueof 0, it indicates that SAO is OFF; a value of one to four indicatesthat one of the four EO categories corresponding to 0°, 90°, 135°, and45° is used; and a value of five indicates that BO is used. In the FIG.24 example, each of the BO and EO types has four SAO offset values(sao_offset[cldx][rx][ry][0] to sao_offset[cldx][rx][ry][3]) that aresignaled.

Generally, a filtering process can use the reconstructed samples of afirst color component as input (e.g., Y or Cb or Cr, or R or G or B) togenerate an output, and the output of the filtering process is appliedon a second color component that can be the same one as the first colorcomponent or that can be another color component that is different fromthe first color component.

In a related example of cross-component filtering (CCF), filtercoefficients are derived based on some mathematical equations. Thederived filter coefficients are signaled from encoder side to thedecoder side, and the derived filter coefficients are used to generateoffsets using linear combinations. The generated offsets are then addedto reconstructed samples as a filtering process. For example, theoffsets are generated based on linear combinations of the filteringcoefficients with luma samples, and the generated offsets are added tothe reconstructed chroma samples. The related example of CCF is based onan assumption of a linear mapping relationship between the reconstructedluma sample values and the delta values between the original andreconstructed chroma samples. However, the mapping between thereconstructed luma sample values and the delta values between theoriginal and reconstructed chroma samples does not necessarily follow alinear mapping process, thus the coding performance of CCF may belimited under the linear mapping relationship assumption.

In some examples, non linear mapping techniques can be used incross-component filtering and/or same color component filtering withoutsignificant signaling overheads. In an example, the non linear mappingtechniques can be used in the cross-component filtering to generatecross-component sample offset. In another example, the non linearmapping techniques can be used in the same color component filtering togenerate local sample offset.

For convenience, a filtering process that uses the non linear mappingtechniques can be referred to as sample offset by non linear mapping(SO-NLM). SO-NLM in the cross-component filtering process can bereferred to as a cross-component sample offset (CCSO). SO-NLM in thesame color component filtering can be referred to as local sample offset(LSO). Filters that use the non linear mapping techniques can bereferred to as non linear mapping based filters. The non linear mappingbased filters can include CCSO filters, LSO filters and the like.

In an example, CCSO and LSO can be used as loop filtering to reducedistortion of reconstructed samples. CCSO and LSO do not rely on thelinear mapping assumption used in the related example CCF. For example,CCSO does not rely on the assumption of linear mapping relationshipbetween the luma reconstructed sample values and the delta valuesbetween the original chroma samples and chroma reconstructed samples.Similarly, LSO does not rely on the assumption of linear mappingrelationship between the reconstructed sample values of a colorcomponent and the delta values between the original samples of the colorcomponent and reconstructed samples of the color component.

In the following description, SO-NLM filtering process is described thatuse the reconstructed samples of a first color component as input (e.g.,Y or Cb or Cr, or R or G or B) to generate an output, and the output ofthe filtering process is applied on a second color component. When thesecond color component is the same color component as the first colorcomponent, the description is applicable for LSO; and when the secondcolor component is different from the first color component, thedescription is applicable for CCSO.

In SO-NLM, a non linear mapping is derived at encoder side. A non linearmapping is between reconstructed samples of a first color component inthe filter support region and offsets to be added to a second colorcomponent in the filter support region. When the second color componentis the same as the first color component, the non linear mapping is usedin LSO; when the second color component is different from the firstcolor component, the non linear mapping is used in CCSO. The domain ofthe non linear mapping is determined by different combinations ofprocessed input reconstructed samples (also referred to as combinationsof possible reconstructed sample values).

Techniques of SO-NLM can be illustrated using a specific example. In thespecific example, reconstructed samples from a first color componentlocated in a filter support area (also referred to as “filter supportregion”) are determined. The filter support area is an area within whichthe filter can be applied, and the filter support area can have anysuitable shape.

FIG. 25 shows an example of a filter support area (2500) according tosome embodiments of the disclosure. The filter support area (2500)includes four reconstructed samples: P0, P1, P2 and P3 of a first colorcomponent. In the FIG. 25 example, the four reconstructed samples canform a cross-shape in the vertical direction and the horizontaldirection, and the center location of the cross-shape is the locationfor the sample to be filtered. A sample at the center location and ofthe same color component as P0-P3 is denoted by C. A sample at thecenter location and of a second color component is denoted by F. Thesecond color component can be the same as the first color component ofP0-P3 or can be different from the first color component of P0-P3.

FIG. 26 shows an example of another filter support area (2600) accordingto some embodiments of the disclosure. The filter support area (2600)includes four reconstructed samples P0, P1, P2 and P3 of a first colorcomponent that form a square shape. In the FIG. 26 example, the centerlocation of the square shape is the location of the sample to befiltered. A sample at the center location and of the same colorcomponent as P0-P3 is denoted by C. A sample at the center location andof a second color component is denoted by F. The second color componentcan be the same as the first color component of P0-P3 or can bedifferent from the first color component of P0-P3.

The reconstructed samples are input to the SO-NLM filter, and aresuitably processed to form filter taps. In an example, the location of areconstructed sample that is an input to the SO-NLM filter is referredto as filter tap location. In a specific example, the reconstructedsamples are processed in following two steps.

In a first step, the delta values respectively between P0-P3 and C arecomputed. For example, m0 denotes the delta value between P0 to C; m1denotes the delta value between P1 to C; m2 denotes the delta valuebetween P2 to C; m3 denotes the delta value between P3 to C.

In a second step, the delta values m0-m3 are further quantized, thequantized values are denoted as d0, d1, d2, d3. In an example, thequantized value can be one of −1, 0, 1 based on a quantization process.For example, a value m can be quantized to −1 when m is smaller than −N(N is a positive value and is referred to as quantization step size);the value m can be quantized to 0 when m is in a range of [−N, N]; andthe value m can be quantized to 1 when m is greater than N. In someexamples, the quantization step size N can be one of 4, 8, 12, 16 andthe like.

In some embodiments, the quantized values d0-d3 are filter taps and canbe used to identify one combination in the filter domain. For example,the filter taps d0-d3 can form a combination in the filter domain. Eachfilter tap can have three quantized values, thus when four filter tapsare used, the filter domain includes 81 (3×3×3×3) combinations.

FIGS. 27A-27C show a table (2700) having 81 combinations according to anembodiment of the disclosure. The table (2700) includes 81 rowscorresponding to 81 combinations. In each row corresponding to acombination, the first column includes an index of the combinations; thesecond column includes the value of filter tap d0 for the combination;the third column includes the value of filter tap d1 for thecombination; the fourth column includes the value of filter tap d2 forthe combination; the fifth column includes the value of filter tap d3for the combination; the six column includes the offset value associatedwith the combination for the non linear mapping. In an example, when thefilter taps d0-d3 are determined, the offset value (denoted by s)associated with the combination of d0-d3 can be determined according tothe table (2700). In an example, offset values s0-s80 are integers, suchas 0, 1, −1, 3, −3, 5, −5, −7, and the like.

In some embodiments, the final filtering process of SO-NLM can beapplied as shown in Eq. (16):f′=clip(f+s)  Eq. (16)where f is the reconstructed sample of the second color component to befiltered, and s is the offset value determined according to filter tapsthat are processing results of reconstructed samples of first colorcomponent, such as using table (2700). The sum of the reconstructedsample F and the offset value s is further clipped into the rangeassociated with bit-depth to determine the final filtered sample f′ ofthe second color component.

It is noted that, in the case of LSO, the second color component in theabove description is the same as the first color component; and, in thecase of CCSO, the second color component in the above description can bedifferent from the first color component.

It is noted that, the above description can be adjusted for otherembodiments of the present disclosure.

In some examples, at the encoder side, the encoding device can derive amapping between reconstructed samples of a first color component in afilter support region and the offsets to be added to reconstructedsamples of a second color component. The mapping can be any suitablelinear or non-linear mapping. Then, the filtering process can be appliedat the encoder side and/or the decoder side based on the mapping. Forexample, the mapping is suitably informed to the decoder (e.g., themapping is included in a coded video bitstream that is transmitted fromthe encoder side to the decoder side), and then the decoder can performthe filtering process based on the mapping.

According to some aspects of the disclosure, performance of the nonlinear mapping based filters, such as the CCSO filters, LSO filters andthe like, depends on filter shape configuration. Using a fixed filtershape configuration may limit the performance of the non linear mappingbased filters. Aspects of the techniques provide techniques ofswitchable filter shape configuration for a non linear mapping basedfilter, such as a CCSO filter, an LSO filter and the like.

According to some aspects of the disclosure, a filter shapeconfiguration (also referred to as filter shape) of a filter can referto properties of a pattern formed by filter tap locations. The patterncan be defined by various parameters, such as a geometry shape of thefilter tap locations, a distance of filter tap locations to a center ofthe pattern, and the like.

In some embodiments, the filter shape configuration of the non linearmapping based filters, such as CCSO filters, LSO filters, and the likecan have a geometry shape of a cross. Specifically, the filter taplocations exist on the top, the bottom, the left, and the right of acenter position of the filter tap locations. The distance (denoted by n)of the filter tap locations to the center of the filter tap locationscan be any suitable positive integer number, such as 1, 2, 3, 4, 5, andthe like in the unit of sample in an example.

FIG. 28 shows an example of a filter shape configuration (2800)according to an embodiment of the disclosure. The filter shapeconfiguration (2800) has a geometry shape of a cross and the distance offilter tap locations to the center of the filter shape configuration(2800) is 1 sample (n=1). In FIG. 28 , each circle is used to representa sample. The center positon is shown by C in FIG. 28 . The filter shapeconfiguration (2800) includes four filter tap locations that are shownby p0, p1, p2 and p3. As shown, the filter tap location p0 is on the topof the center position C; the filter tap location p1 is to the left ofthe center position C; the filter tap location p2 is at the bottom ofthe center position C; and the filter tap location p3 is to the right ofthe center position C. The distance of the filter tap location p0 to thecenter positon C is 1 sample; the distance of the filter tap location p1to the center positon C is 1 sample; the distance of the filter taplocation p2 to the center positon C is 1 sample; and the distance of thefilter tap location p3 to the center positon C is 1 sample.

In an example, to apply a filter of the filter shape configuration(2800) to a sample, the sample to be filtered is located at the centerposition C; a reconstructed sample located at the filter tap location p0is used to derive a first filter tap (d0); a reconstructed samplelocated at the filter tap location p1 is used to derive a second filtertap (d1); a reconstructed sample located at the filter tap location p2is used to derive a third filter tap (d2); and a reconstructed samplelocated at the filter tap location p3 is used to derive a fourth filtertap (d1). Then, the filter taps d0-d3 are used to determine a sampleoffset to be applied to the sample to be filtered.

FIG. 29 shows another example of a filter shape configuration (2900)according to an embodiment of the disclosure. The filter shapeconfiguration (2900) has a geometry shape of a cross and the distance offilter tap locations to the center of the filter shape configuration(2900) is 4 samples (n=4). Specifically, each circle is used torepresent a sample, and the center positon is shown by C in FIG. 29 .The filter shape configuration (2900) includes four filter tap locationsthat are shown by p0, p1, p2 and p3. As shown in FIG. 29 , the filtertap location p0 is on the top of the center position C; the filter taplocation p1 is to the left of the center position C; the filter taplocation p2 is at the bottom of the center position C; and the filtertap location p3 is to the right of the center position C. The distanceof the filter tap location p0 to the center positon C is 4 samples; thedistance of the filter tap location p1 to the center positon C is 4samples; the distance of the filter tap location p2 to the centerpositon C is 4 samples; and the distance of the filter tap location p3to the center positon C is 4 samples.

In an example, to apply a filter of the filter shape configuration(2900) to a sample, the sample to be filtered is located at the centerposition C; a reconstructed sample located at the filter tap location p0is used to derive a first filter tap (d0); a reconstructed samplelocated at the filter tap location p1 is used to derive a second filtertap (d1); a reconstructed sample located at the filter tap location p2is used to derive a third filter tap (d2); and a reconstructed samplelocated at the filter tap location p3 is used to derive a fourth filtertap (d1). Then, the filter taps d0-d3 are used to determine a sampleoffset to be applied to the sample to be filtered.

FIG. 30 shows an example of a filter shape configuration (3000)according to an embodiment of the disclosure. The filter shapeconfiguration (3000) has a geometry shape of a rectangle and thedistance of filter tap locations to the center of the filter taplocations is 1 sample (n=1). Specifically, the center positon is shownby C in FIG. 30 . The filter shape configuration (3000) includes fourfilter tap locations that are shown by q0, q1, q2 and q3. As shown, thefilter tap location q0 is located at top left of the center position C;the filter tap location q1 is located at bottom left of the centerposition C; the filter tap location q2 is located at the bottom right ofthe center position C; and the filter tap location q3 is located at topright of the center position C. The distance of the filter tap locationq0 to the center positon C is 1 sample; the distance of the filter taplocation q1 to the center positon C is 1 sample; the distance of thefilter tap location q2 to the center positon C is 1 sample; and thedistance of the filter tap location q3 to the center positon C is 1sample.

In an example, to apply a filter of the filter shape configuration(3000) to a sample, the sample to be filtered is located at the centerposition C; a reconstructed sample located at the filter tap location q0is used to derive a first filter tap (d0); a reconstructed samplelocated at the filter tap location q1 is used to derive a second filtertap (d1); a reconstructed sample located at the filter tap location q2is used to derive a third filter tap (d2); and a reconstructed samplelocated at the filter tap location q3 is used to derive a fourth filtertap (d1). Then, the filter taps d0-d3 are used to determine a sampleoffset to be applied to the sample to be filtered.

FIG. 31 shows an example of a filter shape configuration (3100)according to an embodiment of the disclosure. The filter shapeconfiguration (3100) has a geometry shape of a rectangle and thedistance of filter tap locations to the center of the filter taplocations is 4 samples (n=4). Specifically, the center positon is shownby C in FIG. 31 . The filter shape configuration (3100) includes fourfilter tap locations that are shown by q0, q1, q2 and q3. As shown, thefilter tap location q0 is located at top left of the center position C;the filter tap location q1 is located at bottom left of the centerposition C; the filter tap location q2 is located at the bottom right ofthe center position C; and the filter tap location q3 is located at topright of the center position C. The distance of the filter tap locationq0 to the center positon C is 4 samples; the distance of the filter taplocation q1 to the center positon C is 4 samples; the distance of thefilter tap location q2 to the center positon C is 4 samples; and thedistance of the filter tap location q3 to the center positon C is 4samples.

In an example, to apply a filter of the filter shape configuration(3100) to a sample, the sample to be filtered is located at the centerposition C; a reconstructed sample located at the filter tap location q0is used to derive a first filter tap (d0); a reconstructed samplelocated at the filter tap location q1 is used to derive a second filtertap (d1); a reconstructed sample located at the filter tap location q2is used to derive a third filter tap (d2); and a reconstructed samplelocated at the filter tap location q3 is used to derive a fourth filtertap (d1). Then, the filter taps d0-d3 are used to determine a sampleoffset to be applied to the sample to be filtered.

According to an aspect of the disclosure, the filter shape configurationof a non linear mapping based filter, such as a CCSO filter, a LSOfilter, and the like can be switchable during reconstruction of a videofrom a coded video bitstream. The non linear mapping based filter canselect one of multiple candidate filter shape configurations, at asuitable level, such as at a picture level, a block level, a slicelevel, a tile level, and the like.

In an embodiment, the multiple candidate filter shape configurations canhave a same geometry shape.

FIG. 32 shows an example (3200) of three candidate filter shapeconfigurations that have the cross geometry shape. The distance of thefilter tap locations to the center by the three candidate filter shapeconfigurations can be different.

Specifically, in FIG. 32 , a center position C and filter tap locationsp0, p1, p2 and p3 form a first candidate filter shape configuration. Thedistance of the filter tap locations p0, p1, p2 and p3 to the centerposition C is 1 sample. The center position C and filter tap locationsp0′, p1′, p2′ and p3′ form a second candidate filter shapeconfiguration. The distance of the filter tap locations p0′, p1′, p2′and p3′ to the center position C is 4 samples. The center position C andfilter tap locations p0″, p1“, p2” and p3″ form a third candidate filtershape configuration. The distance of the filter tap locations p0″, p1“,p2” and p3″ to the center position C is 7 samples.

In some examples, one of the first candidate filter shape configuration,the second candidate filter shape configuration and the third candidatefilter shape configuration can be selected at a suitable level, such asat a picture level, a block level, a slice level, a tile level, and thelike, for use in the sample reconstruction at the suitable level.

FIG. 33 shows an example (3300) of two candidate filter shapeconfigurations that have the cross geometry shape. The distance of thefilter tap locations to the center by the two candidate filter shapeconfigurations can be different.

Specifically, in FIG. 33 , a center position C and filter tap locationsp0, p1, p2 and p3 form a first candidate filter shape configuration. Thedistance of the filter tap locations p0, p1, p2 and p3 to the centerposition C is 1 sample. The center position C and filter tap locationsp0′, p1′, p2′ and p3′ form a second candidate filter shapeconfiguration. The distance of the filter tap locations p0′, p1′, p2′and p3′ to the center position C is 4 samples.

In some examples, one of the first candidate filter shape configuration,and the second candidate filter shape configuration can be selected at asuitable level, such as at a picture level, a block level, a slicelevel, a tile level, and the like, for use in the sample reconstructionat the suitable level.

It is noted that the candidate filter shape configurations can haveother suitable geometry shape.

FIG. 34 shows an example (3400) of two candidate filter shapeconfigurations that have the rectangular geometry shape. The distance ofthe filter tap locations to the center by the two candidate filter shapeconfigurations can be different.

Specifically, in FIG. 34 , a center position C and filter tap locationsq0, q1, q2 and q3 form a first candidate filter shape configuration. Thedistance of the filter tap locations q0, q1, q2 and q3 to the centerposition C is 1 sample. The center position C and filter tap locationsq0′, q1′, q2′ and q3′ form a second candidate filter shapeconfiguration. The distance of the filter tap locations q0′, q1′, q2′and q3′ to the center position C is 4 samples.

In some examples, one of the first candidate filter shape configuration,and the second candidate filter shape configuration can be selected at asuitable level, such as at a picture level, a block level, a slicelevel, a tile level, and the like, for use in the sample reconstructionat the suitable level.

It is also noted that the candidate filter shape configurations can havedifferent geometry shapes.

FIG. 35 shows an example (3500) of four candidate filter shapeconfigurations that have a mixture of cross geometry shape andrectangular geometry shape. The distance of the filter tap locations tothe center by the four candidate filter shape configurations can bedifferent.

Specifically, in FIG. 35 , a center position C and filter tap locationsp0, p1, p2 and p3 form a first candidate filter shape configuration. Thedistance of the filter tap locations p0, p1, p2 and p3 to the centerposition C is 1 sample. The center position C and filter tap locationsp0′, p1′, p2′ and p3′ form a second candidate filter shapeconfiguration. The distance of the filter taps locations p0′, p1′, p2′and p3′ to the center position C is 4 samples. The first candidatefilter shape configuration and the second candidate filter shapeconfiguration have cross geometry shape.

Further, the center position C and filter tap locations q0, q1, q2 andq3 form a third candidate filter shape configuration. The distance ofthe filter tap locations q0, q1, q2 and q3 to the center position C is 1sample. The center position C and filter tap locations q0′, q1 q2′ andq3′ form a fourth candidate filter shape configuration. The distance ofthe filter tap locations q0′, q1′, q2′ and q3′ to the center position Cis 4 sample. The third candidate filter shape configuration and thefourth candidate filter shape configuration have rectangular geometryshape.

In some examples, one of the first candidate filter shape configuration,the second candidate filter shape configuration, the third candidatefilter shape configuration and the fourth candidate filter shapeconfiguration can be selected at a suitable level, such as at a picturelevel, a block level, a slice level, a tile level, and the like, for usein the sample reconstruction at the suitable level.

According to an aspect of the disclosure, the selection of a filtershape configuration from multiple candidate filter shape configurationscan be signalled in the coded video bitstream from the encoder to thedecoder.

In one embodiment, the switching of the filter shape configuration forthe non linear mapping based filter (e.g., CCSO filter, LSO filter) isat a picture-level. In an example, an index indicative of the selectedfilter shape configuration from multiple candidate filter shapeconfigurations is signaled for each picture in the coded videobitstream.

In one embodiment, the switching of filter shape configuration for thenon linear mapping based filter (e.g., CCSO filter, LSO filter) is atblock-level. The block may be interpreted as a prediction block, acoding block, or a coding unit, i.e. CU, a CTU block, or super block, ora filtering unit (FU). In an example, an index indicative of theselected filter shape configuration from multiple candidate filter shapeconfigurations is signaled for each block in the coded video bitstream.

It is noted that, in some embodiment, the index indicative of theselected filter shape configuration can be signaled in high levelsyntax, such as APS, slice header, a frame header, PPS, SPS, VPS, andthe like.

According to an aspect of the disclosure, samples at the filter taplocations can be pre-processed before used as input to the non linearmapping based filter, such as the CCSO filter, the LSO filter, and thelike.

In an embodiment, weighted average of sample values at the filter tapscan be calculated.

FIG. 36 shows an example (3600) of pre-processing according to anembodiment of the disclosure. The example (3600) includes eight filtertap locations p0-p7 as shown in FIG. 36 . In an example, an average ofsamples at the filter tap locations p0 and p1 is calculated and denotedas p0′, an average of samples at the filter tap locations p2 and p3 iscalculated and denoted as p1′, an average of samples at the filter taplocations p4 and p5 is calculated and denoted as p2′, and an average ofsamples at the filter tap locations p6 and p7 is calculated and denotedas p3′. Then, p0′-p3′ and c are used as the input of a non linearmapping based filter, such as a CCSO filter, an LSO filter and the like.

It is noted that the average calculation can be weighted average. Forexample, when calculate the average of samples at the filter taplocations p0 and p1, the sample at p0 and the sample at p1 can beweighed differently.

In another embodiment, a pre-filtering process can be applied to thesample located at the filter taps.

FIG. 37 shows an example (3700) of pre-processing according to anembodiment of the disclosure. the example (3700) includes four filtertap locations p0, p1, p2 and p3. In an example, a filtering(pre-filtering) process is applied to a sample at a filter tap locationbased on samples located close (e.g., adjacent or within K sampledistance, K is a positive integer) to the filter tap location.

For example, a first filtering (pre-filtering) process applied to afirst sample at the filter tap location p0 based on first samples atadjacent locations q0-q3; a second filtering (pre-filtering) processapplied to a second sample at the filter tap location p1 based on secondsamples at adjacent locations r0-r3; a third filtering (pre-filtering)process applied to a third sample at the filter tap location p2 based onthird samples at adjacent locations s0-s3; a fourth filtering(pre-filtering) process applied to a fourth sample at the filter taplocation p3 based on fourth samples at adjacent locations t0-t3. Then,the filtered first sample, the filtered second sample, the filteredthird sample, and the filtered fourth sample can be used as the input tothe non-linear mapping based filter, such as the CCSO filter and the LSOfilter.

It is noted that the pre-filtering can be performed by any suitablefilter, linear filter or non-linear filter.

FIG. 38 shows a flow chart outlining a process (3800) according to anembodiment of the disclosure. The process (3800) can be used toreconstruct a video carried in a coded video bitstream. When the termblock is used, block may be interpreted as a prediction block, a codingunit, a luma block, a chroma block, or the like. In various embodiments,the process (3800) are executed by processing circuitry, such as theprocessing circuitry in the terminal devices (310), (320), (330) and(340), the processing circuitry that performs functions of the videoencoder (403), the processing circuitry that performs functions of thevideo decoder (410), the processing circuitry that performs functions ofthe video decoder (510), the processing circuitry that performsfunctions of the video encoder (603), and the like. In some embodiments,the process (3800) is implemented in software instructions, thus whenthe processing circuitry executes the software instructions, theprocessing circuitry performs the process (3800). The process starts at(S3801) and proceeds to (S3810).

At (S3810), a first sample in a video that is carried in a coded videobitstream is reconstructed based on a non linear mapping based filterwith a first filter shape configuration.

At (S3820), a switch from the first filter shape configuration to asecond filter shape configuration is determined. The second filter shapeconfiguration is different from the first filter shape configuration. Insome examples, the difference between the first filter shapeconfiguration and the second filter shape configuration can be ageometry shape of filter tap locations, and can be a distance from thefilter tap locations to a center of the filter tap locations.

The geometry shape of filter tap locations can be a cross geometry shapeor can be a rectangular geometry shape. The first filter shapeconfiguration and the second filter shape configuration can havedifferent geometry shapes of filter tap locations, or can have a samegeometry shape of filter tap locations. In some examples, the firstfilter shape configuration and the second filter shape configurationhave a same geometry shape, but the distance from the filter taplocations to a center of the filter tap locations is different for thefirst filter shape configuration and the second filter shapeconfiguration.

In some examples, an index is decoded from the coded video bitstreamthat carries the video. The index is indicative of the second filtershape configuration. Then, the switch from the first filter shapeconfiguration to the second filter shape configuration is determinedbased on the index.

In an example, the index is signaled at a picture level, and the switchfrom the first filter shape configuration to the second filter shapeconfiguration is determined at the picture level. The first sample is ina first picture of the video, the second sample is in a second pictureof the video.

In another example, the index is signaled at a block level, and theswitch from the first filter shape configuration to the second filtershape configuration is determined at the block level. The first sampleis in a first block in a picture of the video, the second sample is in asecond block in the picture of the video.

In some examples, the index can be decoded from a signaling in a highlevel syntax, such as in a video parameter set (VPS), in a sequenceparameter set (SPS), in a picture parameter set (PPS), in an adaptationparameter set (APS), in a slice header, in a tile header, in a frameheader and the like.

At (S3830), a second sample in the video is reconstructed based on thenon linear mapping based filter with the second filter shapeconfiguration.

The process (3800) proceeds to (S3899), and terminates.

It is noted that, in some examples, the non linear mapping based filteris a cross-component sample offset (CCSO) filter, and in some otherexamples, the non linear mapping based filter is a local sample offset(LSO) filter.

It is also noted that the sample values as the input to the non linearmapping based filter can be pre-processed. For example, to reconstructthe first sample, a pre-processing operation can be performed on samplesat filter tap locations corresponding to the first filter shapeconfiguration, the pre-processing operation can generate pre-processedsamples. Then, the pre-processed samples are used as input to the nonlinear mapping based filter and an offset to apply on the first samplecan be determined based on the pre-processed samples. In an example, thepre-processing operation is a weighted averaging operation. For example,an average sample value at two or more filter tap locations can becalculated to derive a pre-processed sample. In another example, thepre-processing operation is a filtering operation. For example, a filteris applied on a sample at a filter tap location to generate a filteredsample as a pre-processed sample. The filter can be any suitable filter,such as a linear filter, a non linear filter, and the like.

The process (3800) can be suitably adapted. Step(s) in the process(3800) can be modified and/or omitted. Additional step(s) can be added.Any suitable order of implementation can be used.

Embodiments in the disclosure may be used separately or combined in anyorder. Further, each of the methods (or embodiments), an encoder, and adecoder may be implemented by processing circuitry (e.g., one or moreprocessors or one or more integrated circuits). In one example, the oneor more processors execute a program that is stored in a non-transitorycomputer-readable medium.

The techniques described above, can be implemented as computer softwareusing computer-readable instructions and physically stored in one ormore computer-readable media. For example, FIG. 39 shows a computersystem (3900) suitable for implementing certain embodiments of thedisclosed subject matter.

The computer software can be coded using any suitable machine code orcomputer language, that may be subject to assembly, compilation,linking, or like mechanisms to create code comprising instructions thatcan be executed directly, or through interpretation, micro-codeexecution, and the like, by one or more computer central processingunits (CPUs), Graphics Processing Units (GPUs), and the like.

The instructions can be executed on various types of computers orcomponents thereof, including, for example, personal computers, tabletcomputers, servers, smartphones, gaming devices, internet of thingsdevices, and the like.

The components shown in FIG. 39 for computer system (3900) are exemplaryin nature and are not intended to suggest any limitation as to the scopeof use or functionality of the computer software implementingembodiments of the present disclosure. Neither should the configurationof components be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary embodiment of a computer system (3900).

Computer system (3900) may include certain human interface inputdevices. Such a human interface input device may be responsive to inputby one or more human users through, for example, tactile input (such as:keystrokes, swipes, data glove movements), audio input (such as: voice,clapping), visual input (such as: gestures), olfactory input (notdepicted). The human interface devices can also be used to capturecertain media not necessarily directly related to conscious input by ahuman, such as audio (such as: speech, music, ambient sound), images(such as: scanned images, photographic images obtain from a still imagecamera), video (such as two-dimensional video, three-dimensional videoincluding stereoscopic video).

Input human interface devices may include one or more of (only one ofeach depicted): keyboard (3901), mouse (3902), trackpad (3903), touchscreen (3910), data-glove (not shown), joystick (3905), microphone(3906), scanner (3907), camera (3908).

Computer system (3900) may also include certain human interface outputdevices. Such human interface output devices may be stimulating thesenses of one or more human users through, for example, tactile output,sound, light, and smell/taste. Such human interface output devices mayinclude tactile output devices (for example tactile feedback by thetouch-screen (3910), data-glove (not shown), or joystick (3905), butthere can also be tactile feedback devices that do not serve as inputdevices), audio output devices (such as: speakers (3909), headphones(not depicted)), visual output devices (such as screens (3910) toinclude CRT screens, LCD screens, plasma screens, OLED screens, eachwith or without touch-screen input capability, each with or withouttactile feedback capability—some of which may be capable to output twodimensional visual output or more than three dimensional output throughmeans such as stereographic output; virtual-reality glasses (notdepicted), holographic displays and smoke tanks (not depicted)), andprinters (not depicted).

Computer system (3900) can also include human accessible storage devicesand their associated media such as optical media including CD/DVD ROM/RW(3920) with CD/DVD or the like media (3921), thumb-drive (3922),removable hard drive or solid state drive (3923), legacy magnetic mediasuch as tape and floppy disc (not depicted), specialized ROM/ASIC/PLDbased devices such as security dongles (not depicted), and the like.

Those skilled in the art should also understand that term “computerreadable media” as used in connection with the presently disclosedsubject matter does not encompass transmission media, carrier waves, orother transitory signals.

Computer system (3900) can also include an interface (3954) to one ormore communication networks (3955). Networks can for example bewireless, wireline, optical. Networks can further be local, wide-area,metropolitan, vehicular and industrial, real-time, delay-tolerant, andso on. Examples of networks include local area networks such asEthernet, wireless LANs, cellular networks to include GSM, 3G, 4G, 5G,LTE and the like, TV wireline or wireless wide area digital networks toinclude cable TV, satellite TV, and terrestrial broadcast TV, vehicularand industrial to include CANBus, and so forth. Certain networkscommonly require external network interface adapters that attached tocertain general purpose data ports or peripheral buses (3949) (such as,for example USB ports of the computer system (3900)); others arecommonly integrated into the core of the computer system (3900) byattachment to a system bus as described below (for example Ethernetinterface into a PC computer system or cellular network interface into asmartphone computer system). Using any of these networks, computersystem (3900) can communicate with other entities. Such communicationcan be uni-directional, receive only (for example, broadcast TV),uni-directional send-only (for example CANbus to certain CANbusdevices), or bi-directional, for example to other computer systems usinglocal or wide area digital networks. Certain protocols and protocolstacks can be used on each of those networks and network interfaces asdescribed above.

Aforementioned human interface devices, human-accessible storagedevices, and network interfaces can be attached to a core (3940) of thecomputer system (3900).

The core (3940) can include one or more Central Processing Units (CPU)(3941), Graphics Processing Units (GPU) (3942), specialized programmableprocessing units in the form of Field Programmable Gate Areas (FPGA)(3943), hardware accelerators for certain tasks (3944), graphics adapter(3950), and so forth. These devices, along with Read-only memory (ROM)(3945), Random-access memory (3946), internal mass storage such asinternal non-user accessible hard drives, SSDs, and the like (3947), maybe connected through a system bus (3948). In some computer systems, thesystem bus (3948) can be accessible in the form of one or more physicalplugs to enable extensions by additional CPUs, GPU, and the like. Theperipheral devices can be attached either directly to the core's systembus (3948), or through a peripheral bus (3949). In an example, a display(3910) can be connected to the graphics adapter (3950). Architecturesfor a peripheral bus include PCI, USB, and the like.

CPUs (3941), GPUs (3942), FPGAs (3943), and accelerators (3944) canexecute certain instructions that, in combination, can make up theaforementioned computer code. That computer code can be stored in ROM(3945) or RAM (3946). Transitional data can be also be stored in RAM(3946), whereas permanent data can be stored for example, in theinternal mass storage (3947). Fast storage and retrieve to any of thememory devices can be enabled through the use of cache memory, that canbe closely associated with one or more CPU (3941), GPU (3942), massstorage (3947), ROM (3945), RAM (3946), and the like.

The computer readable media can have computer code thereon forperforming various computer-implemented operations. The media andcomputer code can be those specially designed and constructed for thepurposes of the present disclosure, or they can be of the kind wellknown and available to those having skill in the computer software arts.

As an example and not by way of limitation, the computer system havingarchitecture (3900), and specifically the core (3940) can providefunctionality as a result of processor(s) (including CPUs, GPUs, FPGA,accelerators, and the like) executing software embodied in one or moretangible, computer-readable media. Such computer-readable media can bemedia associated with user-accessible mass storage as introduced above,as well as certain storage of the core (3940) that are of non-transitorynature, such as core-internal mass storage (3947) or ROM (3945). Thesoftware implementing various embodiments of the present disclosure canbe stored in such devices and executed by core (3940). Acomputer-readable medium can include one or more memory devices orchips, according to particular needs. The software can cause the core(3940) and specifically the processors therein (including CPU, GPU,FPGA, and the like) to execute particular processes or particular partsof particular processes described herein, including defining datastructures stored in RAM (3946) and modifying such data structuresaccording to the processes defined by the software. In addition or as analternative, the computer system can provide functionality as a resultof logic hardwired or otherwise embodied in a circuit (for example:accelerator (3944)), which can operate in place of or together withsoftware to execute particular processes or particular parts ofparticular processes described herein. Reference to software canencompass logic, and vice versa, where appropriate. Reference to acomputer-readable media can encompass a circuit (such as an integratedcircuit (IC)) storing software for execution, a circuit embodying logicfor execution, or both, where appropriate. The present disclosureencompasses any suitable combination of hardware and software.

APPENDIX A: ACRONYMS

JEM: joint exploration model

VVC: versatile video coding

BMS: benchmark set

MV: Motion Vector

HEVC: High Efficiency Video Coding

MPM: most probable mode

WAIP: Wide-Angle Intra Prediction

SEI: Supplementary Enhancement Information

VUI: Video Usability Information

GOPs: Groups of Pictures

TUs: Transform Units,

PUs: Prediction Units

CTUs: Coding Tree Units

CTBs: Coding Tree Blocks

PBs: Prediction Blocks

HRD: Hypothetical Reference Decoder

SDR: standard dynamic range

SNR: Signal Noise Ratio

CPUs: Central Processing Units

GPUs: Graphics Processing Units

CRT: Cathode Ray Tube

LCD: Liquid-Crystal Display

OLED: Organic Light-Emitting Diode

CD: Compact Disc

DVD: Digital Video Disc

ROM: Read-Only Memory

RAM: Random Access Memory

ASIC: Application-Specific Integrated Circuit

PLD: Programmable Logic Device

LAN: Local Area Network

GSM: Global System for Mobile communications

LTE: Long-Term Evolution

CANBus: Controller Area Network Bus

USB: Universal Serial Bus

PCI: Peripheral Component Interconnect

FPGA: Field Programmable Gate Areas

SSD: solid-state drive

IC: Integrated Circuit

CU: Coding Unit

PDPC: Position Dependent Prediction Combination

ISP: Intra Sub-Partitions

SPS: Sequence Parameter Setting

While this disclosure has described several exemplary embodiments, thereare alterations, permutations, and various substitute equivalents, whichfall within the scope of the disclosure. It will thus be appreciatedthat those skilled in the art will be able to devise numerous systemsand methods which, although not explicitly shown or described herein,embody the principles of the disclosure and are thus within the spiritand scope thereof.

What is claimed is:
 1. A method for filtering in video decoding,comprising: reconstructing, by a processor, a first sample in a videocarried in a coded video bitstream based on a non linear mapping basedfilter with a first filter shape configuration; determining, by theprocessor, a switch from the first filter shape configuration to asecond filter shape configuration, the first filter shape configurationand the second filter shape configuration including a same number offilter taps, and an offset distance of filter tap locations from acenter of the first filter shape configuration being different from anoffset distance of filter tap locations from a center of the secondfilter shape configuration; and reconstructing, by the processor, asecond sample in the video based on the non linear mapping based filterwith the second filter shape configuration.
 2. The method of claim 1,wherein the non linear mapping based filter includes at least one of across-component sample offset (CCSO) filter and a local sample offset(LSO) filter.
 3. The method of claim 1, wherein the first filter shapeconfiguration further differs from the second filter shape configurationby a geometry shape of the filter tap locations.
 4. The method of claim1, wherein the first filter shape configuration and the second filtershape configuration respectively have at least one of a cross geometryshape of filter tap locations and a rectangular geometry shape of filtertap locations.
 5. The method of claim 1, wherein the first filter shapeconfiguration and the second filter shape configuration have a samegeometry shape.
 6. The method of claim 1, further comprising: decodingan index from the coded video bitstream that carries the video, theindex being indicative of the second filter shape configuration; anddetermining the switch from the first filter shape configuration to thesecond filter shape configuration based on the index.
 7. The method ofclaim 6, further comprising: determining the switch from the firstfilter shape configuration to the second filter shape configuration at apicture level, and the first sample being in a first picture of thevideo, the second sample being in a second picture of the video.
 8. Themethod of claim 6, further comprising: determining the switch from thefirst filter shape configuration to the second filter shapeconfiguration at a block level, and the first sample being in a firstblock in a picture of the video, the second sample being in a secondblock in the picture of the video.
 9. The method of claim 6, furthercomprising: decoding the index from a syntax signaling of at least oneof a block level, a video parameter set (VPS), a sequence parameter set(SPS), a picture parameter set (PPS), an adaptation parameter set (APS),a slice header, a tile header and a frame header.
 10. The method ofclaim 1, wherein the reconstructing the first sample in the video basedon the non linear mapping based filter with the first filter shapeconfiguration further comprises: performing a pre-processing operationon samples at the filter tap locations corresponding to the first filtershape configuration to generate pre-processed samples; and determiningthe offset distance to apply on the first sample based on thepre-processed samples.
 11. The method of claim 10, wherein theperforming the pre-processing operation on the samples at the filter taplocations corresponding to the first filter shape configuration togenerate the pre-processed samples further comprises at least one of:calculating an average sample value at two or more of the filter taplocations as a pre-processed sample; and applying a filter on a sampleat a filter tap location of the filter tap locations to generate afiltered sample as the pre-processed sample.
 12. An apparatus for videodecoding, comprising processing circuitry configured to: reconstruct afirst sample in a video carried in a coded video bitstream based on anon linear mapping based filter with a first filter shape configuration;determine a switch from the first filter shape configuration to a secondfilter shape configuration, the first filter shape configuration and thesecond filter shape configuration including a same number of filtertaps, and an offset distance of filter tap locations from a center ofthe first filter shape configuration being different from an offsetdistance of filter tap locations from a center of the second filtershape configuration; and reconstruct a second sample in the video basedon the non linear mapping based filter with the second filter shapeconfiguration.
 13. The apparatus of claim 12, wherein the non linearmapping based filter includes at least one of a cross-component sampleoffset (CCSO) filter and a local sample offset (LSO) filter.
 14. Theapparatus of claim 12, wherein the first filter shape configurationfurther differs from the second filter shape configuration by a geometryshape of the filter tap locations.
 15. The apparatus of claim 12,wherein the first filter shape configuration and the second filter shapeconfiguration respectively have at least one of a cross geometry shapeof filter tap locations and a rectangular geometry shape of filter taplocations.
 16. The apparatus of claim 12, wherein the first filter shapeconfiguration and the second filter shape configuration have a samegeometry shape.
 17. The apparatus of claim 12, wherein the processingcircuitry is further configured to: decode an index from the coded videobitstream that carries the video, the index being indicative of thesecond filter shape configuration; and determine the switch from thefirst filter shape configuration to the second filter shapeconfiguration based on the index.
 18. The apparatus of claim 17, whereinthe processing circuitry is further configured to: determine the switchfrom the first filter shape configuration to the second filter shapeconfiguration at a picture level, and the first sample being in a firstpicture of the video, the second sample being in a second picture of thevideo.
 19. The apparatus of claim 17, wherein the processing circuitryis further configured to: determine the switch from the first filtershape configuration to the second filter shape configuration at a blocklevel, and the first sample being in a first block in a picture of thevideo, the second sample being in a second block in the picture of thevideo.
 20. The apparatus of claim 17, wherein the processing circuitryis further configured to: decode the index from a syntax signaling of atleast one of a block level, a video parameter set (VPS), a sequenceparameter set (SPS), a picture parameter set (PPS), an adaptationparameter set (APS), a slice header, a tile header and a frame header.